IoT

MQTT is an OASIS standard messaging protocol for the Internet of Things (IoT) and one of the protocols supported by akenza. It is designed as an extremely lightweight publish/subscribe messaging protocol that is ideal for connecting remote devices with a small code footprint and minimal network bandwidth. MQTT is used in various industries. To run this project, we used akenza as an IoT platform, as it runs an open-source MQTT broker from Eclipse Mosquitto. By using a combination of MQTT and API functionalities, we have been able to automatically create Digital Twins for our device. As Hardware, we have chosen an Arduino Uno WiFi Rev2. 1. Configure the Arduino Device 1.1 Set up the WiFi Connection To have the Arduino Uno Wifi able to connect to WiFi, we used the WiFiNINA library, available in the Library Manager of Arduino IDE. 1.1.1 Manage Username and Password To manage Username and Password, we have created an additional header file called arudino_secrets.h #define SECRET_SSID "<your username>" #define SECRET_PASS "<your password>" 1.1.2 WiFi Connection Code The code to connect Arduino to WiFi is reported as below: #include <WiFiNINA.h> #include "arduino_secrets.h" ///////please enter your sensitive data in the Secret tab/arduino_secrets.h char ssid[] = SECRET_SSID; // your network SSID (name) char pass[] = SECRET_PASS; // your network password (use for WPA, or use as key for WEP) WiFiClient wifiClient; void setup() { //Initialize serial and wait for port to open: Serial.begin(9600); while (!Serial) { ; // wait for serial port to connect. Needed for native USB port only } // attempt to connect to Wifi network: Serial.print("Attempting to connect to WPA SSID: "); Serial.println(ssid); while (WiFi.begin(ssid, pass) != WL_CONNECTED) { // failed, retry Serial.print("."); delay(5000); } Serial.println("You're connected to the network"); Serial.println(); } void loop() {} 1.2 Set up the MQTT Connection to akenza For security reasons, akenza only supports authenticated connections via MQTT. For this, we have chosen as library PubSubClient to manage our MQTT connection. This enables us to use username and passwords in our connection string. #include <PubSubClient.h> //MQTTClient mqttClient(WiFiClient); char host[] = "mqtt.akenza.io"; char clientid[] = "Arduino"; char username[] = "<copy from Akenza Device Api configuration>"; char password[] = "<copy from Akenza Device Api configuration>"; char outTopic[] = "<copy from Akenza Device Api configuration>"; PubSubClient client(host, 1883, callback, wifiClient); void setup() { if (client.connect(host, username, password)) { Serial.print("Connected to "); Serial.println(host); Serial.println(); boolean r = client.subscribe(outTopic); Serial.print("Subscribed to "); Serial.println(outTopic); Serial.println(); } else { // connection failed // mqttClient.state() will provide more information // on why it failed. Serial.print("Connection failed: "); Serial.println(client.state()); Serial.println(); } } Akenza accepts messages in JSON format for MQTT connections. To build up a well-formed JSON object, we make use of the ArduinoJson library. #include <ArduinoJson.h> void loop() { StaticJsonDocument<256> doc; doc["Temperature"] = 22; doc["Humidity"] = 68; doc["Light"] = 96; // Add an array JsonArray data = doc.createNestedArray("data"); data.add(48); data.add(2.3); char out[128]; int b =serializeJson(doc, out); Serial.print("publishing bytes = "); Serial.println(b,DEC); boolean rc = client.publish(outTopic, out); // The above line prints: // {"sensor":"gps","time":1351824120,"data":[48.756080,2.302038]} delay(5000); client.loop(); } Please note that these are just examples of data; if you would like to send to the cloud data coming from a sensor, the code has to be adapted accordingly. 2. Connect the Arduino device via MQTT on akenza 2.1 Creating a Secret To safely communicate with akenza, a secret must be generated that has to be provided in the topic structure of the uplink request. This step has to be performed for all devices with the same connection parameters which you want to connect. Each device will be uniquely identified by a specific ID accordingly. A secret will be generated after the creation of the MQTT device connector on the Data Flow. 2.1.1 Setting up an MQTT Device Connector on akenza Go to Data Flow in the menu and select Create Data Flow. Choose MQTT as a device connector. As Device Type, select Passthrough to receive data in the same format as sent from your MQTT device. Choose one or multiple Output Connectors of your choice. There are several options to choose from. In this tutorial, we choose the Akenza DB. 2.2 Create an MQTT Device To create a new MQTT device, select Create Device within the menu of the Asset Inventory. Add a device name and optionally a description, Asset Tags, and Custom Fields. Select Next and choose your created MQTT- Data Flow. Select Proceed. Generate a random ID for this device by clicking Generate ID. Finish the process by clicking on the button Create Device. Your device will be now displayed on the Asset Inventory Overview. 2.3 Set up the Arduino Device As a next step, the Arduino device has to be now configured to send data to the MQTT Broker of akenza. Go to Asset Inventory and use the filter to search for your device. Open the device detail page by selecting your device. Within API-Configuration, all the required information is available to set up the device as an MQTT- client. 3. Final Result Now you have all the elements needed to set up your code on Arduino and stream data via MQTT to akenza. The final code is reported as below: #include <SPI.h> #include <PubSubClient.h> #include <WiFiNINA.h> #include <ArduinoJson.h> #include "arduino_secrets.h" ///////please enter your sensitive data in the Secret tab/arduino_secrets.h char ssid[] = SECRET_SSID; // your network SSID (name) char pass[] = SECRET_PASS; // your network password (use for WPA, or use as key for WEP) char host[] = "mqtt.akenza.io"; char clientid[] = "Arduino"; char username[] = "0783ddd64683f579"; char password[] = "bd604gmgit0x7kilc8puok3g2rxsldl2"; char outTopic[] = "/up/bd604gmgit0x7kilc8puok3g2rxsldl2/id/99E77F4ECC728656"; //set interval for sending messages (milliseconds) const long interval = 8000; unsigned long previousMillis = 0; int count = 0; //receive data void callback(char* topic, byte* payload, unsigned int length) { char str[length+1]; Serial.print("Message arrived ["); Serial.print(topic); Serial.print("] "); int i=0; for (i=0;i<length;i++) { Serial.print((char)payload[i]); str[i]=(char)payload[i]; } str[i] = 0; // Null termination Serial.println(); StaticJsonDocument <256> doc; deserializeJson(doc,payload); // deserializeJson(doc,str); can use string instead of payload const char* sensor = doc["sensor"]; long time = doc["time"]; float latitude = doc["data"][0]; float longitude = doc["data"][1]; Serial.println("latitude ="); Serial.println(latitude,2); Serial.println(sensor); } WiFiClient wifiClient; PubSubClient client(host, 1883, callback, wifiClient); void setup() { //Initialize serial and wait for port to open: Serial.begin(9600); while (!Serial) { ; // wait for serial port to connect. Needed for native USB port only } // attempt to connect to Wifi network: Serial.print("Attempting to connect to WPA SSID: "); Serial.println(ssid); while (WiFi.begin(ssid, pass) != WL_CONNECTED) { // failed, retry Serial.print("."); delay(5000); } Serial.println("You're connected to the network"); Serial.println(); if (client.connect(host, username, password)) { Serial.print("Connected to "); Serial.println(host); Serial.println(); boolean r = client.subscribe(outTopic); Serial.print("Subscribed to "); Serial.println(outTopic); Serial.println(); } else { // connection failed Serial.println("Connection failed "); Serial.println(client.state()); Serial.println(); } } void loop() { StaticJsonDocument<256> doc; doc["Temperature"] = 22; doc["Humidity"] = 68; doc["Light"] = 96; // Add an array JsonArray data = doc.createNestedArray("data"); data.add(48); data.add(2.3); char out[128]; int b =serializeJson(doc, out); Serial.print("publishing bytes = "); Serial.println(b,DEC); boolean rc = client.publish(outTopic, out); // The above line prints: // {"sensor":"gps","time":1351824120,"data":[48.756080,2.302038]} delay(5000); client.loop(); } It automatically decodes the received JSON and visualizes data received from the Arduino device. Incoming data can be viewed on the Device Detail Page within Message Logs. Incoming data are visualized on Data Overview as Device Data KPIs and also on the History chart.

The timely and perfect conveyance of resources to people is the cornerstone of logistics systems. Despite technological developments, manufacturers, suppliers, and distributors are continually seeking effective alternatives to get their products to potential clients. Businesses may use logistic automation to obtain a competitive advantage over their competitors in this area. Logistics is one of the large businesses that continuously supports other critical sectors, and we all rely on it in some manner in our everyday lives. This business is valued at more than 5.7 trillion euros and is regarded to be the bedrock of global commerce, and automation has always been a strong fit for the logistics industry. Logistics Automation Benefits in Disparate System Remember when word flashed across the world that a massive cargo ship became stranded and shut the whole Suez Canal, causing billions of dollars in income loss and price inflation for numerous products? Such scenarios may be avoided by incorporating automation technologies such as RPA bots, Intelligent Document Processing (IDP) systems, and full hyperautomation platforms that manage end-to-end processes involving both software and human efforts. Automation’s most obvious benefit is that it reduces labor, but it is also used to save energy and materials, as well as to increase quality, accuracy, and precision. However, there are some significant benefits to logistic automation that should not be underestimated. Some of them include: Speed and Scalability With such comprehensive logistics automation solutions in your transportation management system (TMS), there are no more resources required to manage your logistics, freight, and transportation departments. Even if your company expands and delivers more freight, TMS will effortlessly manage and record any new user information into the system. Furthermore, thanks to a wonderful freight accounting automation mechanism incorporated into the TMS, all freight bills can be merged into a single weekly invoice — independent of the number of shipments received by each location. More Refined Customer Service Poor customer service in any field will result in the loss of a company’s existence as well as potential consumers. TMS logistics automation solutions can provide your clients with the necessary ease. They can obtain real-time tracking, insurance, vehicle pickup, and freight accounting. Furthermore, logistics automation would make it easier to provide more comfort for customers by notifying them of the true cost of their freight and when they can anticipate it to arrive. Reduce Costly Errors The expense of freight and transportation is a big source of concern. Erroneous data entry in shipments might result in paying twice for transportation or increased freight rates due to incorrect freight commodity classification. Implementing logistics automation allows for features such as commodity integration through your ERP (Enterprise Resource Planning) system and access to your address book, as well as details such as automatic storage, entry of fuel surcharges, and accessorials, which eliminates the need to worry about entering incorrect information. Avoiding such petty human errors can minimize the unwanted cost which ultimately leads to seamless operations. Organizational Control In logistics, monitoring transportation is one of the hardest challenges to tackle. Organizations must keep a close eye on freight management, which is where transportation management systems can help. You may easily take control of the complete activities including the flow of products with TMS. Furthermore, this shipping software is versatile enough to meet all of the company’s requirements while reducing costs. ERP systems are sufficiently strong to persuade both internal and external users to adhere to policies. As a result, output and efficiency both improve. More Inventory Visibility and Control It is essential to be operationally proficient, especially in transportation and shipping. And that can only be accomplished with comprehensive inventory control. Maintaining a record of current inventories, requests, and deliveries on their way is also a vital role for companies. Automation integration in logistics can assist in inventory tracking and maintaining a designated repository for all information. ERP software, for example, provides you with the tools and information you need to handle all incoming and outgoing orders. It also aids in the analysis of remaining inventory and out-of-stock products. Furthermore, it includes extensive information regarding the stockroom and helps executives and decision-makers make better judgments in order to boost profitability. Upcoming Revolutionized Trends with Logistic Automation Adding advanced automation technologies in logistic operations will definitely impact how things will function in the near future. Here are some top trends that are expected to happen in the logistics sector that organizations must be aware of: Extensive Implementation of RPA in Logistics Employees in call centers are responsible for arranging dock-door schedules, arriving and leaving cargo, and product movements inside a warehouse. Moreover, warehouse personnel are required to input and check data. There are many moving parts, and navigating them requires a lot of keystrokes, from transferring data across devices to entering into supplier portals to changing clients. RPA is the best fit technology to automate these operations, minimizing keystrokes, rework, and other inefficiencies in call centers. Automated Digital Walkthrough Between Customers and Portals Logistics companies spend a significant amount of time navigating customer and supplier portals. RPA can handle many repetitive operations linked with these portals, whether they are inbound or outbound orders. With such a technology deployment, a streamlined workflow is something that can be achieved. Finding Automation Opportunities With Process Mining Automation just distributes an inefficient process. Using process mining tools, managers may get an exact representation of how a task is completed step-by-step. You may find wasteful processes down to the keystroke level by thoroughly mapping the process. Conclusion Automation — when used appropriately — can do wonders for global businesses. We have already seen multiple industries such as manufacturing and e-commerce benefiting from automation services in their process. Automation in logistics undoubtedly will aid shippers in increasing efficiency, minimizing waste, and, most significantly, saving money.

Smartphones continue to evolve the functionality of connected devices. Mobile apps now serve as the principal means of device control in the Internet of Things (IoT). Instead of hardwired screens and buttons, today’s developers are offloading the vast majority of user interfaces to our handheld companions. In this way, app developers must ensure their designs are user-friendly and technically sound. And, with more than one billion of them around the world, this means developers need to consider the ins and outs of the iPhone. Apple’s flagship device counts a unique operating system — iOS — that should not be ignored in app rollouts. So, how do you go about programming IoT with iOS? What’s more, how do you build an IoT app on iOS? Let’s look at five steps for developers to successfully build IoT apps on IoS. Step 1: Learn Xcode and Swift When developing an app, you have to choose whether to do it natively, hybrid, or cross-platform: Native: You use languages that are native to the OS the app is going to run on Hybrid: Utilizing plugins to make another non-native code work in a native app Cross-platform: This means using non-native code The best of these options – if your app is only for one operating system – is native development. This is because it lets you access OS features – such as GPS or the camera – and gives your app better performance. When developing natively for iOS, you are going to want to use the native Xcode. Xcode is an Integrated Development Environment (IDE) for macOS that contains a set of tools created by Apple for the development of software for multiple apple operating systems, including MacOS, iOS, watchOS and tvOS. Xcode is the only legitimate program you can use to make native Apple apps, so learning Xcode is going to be necessary for developing an iOS IoT app. This IDE lets you test your app with either a simulator or your own iOS device, so its advantage for developing in iOS is immediately noticeable. Xcode is completely free for users of the latest macOS and can be found on the Mac App Store. This means that you need a Mac computer to work on Xcode. That being said, if you are a Windows or Linux user, there is a way around this. Simply set up a Virtual Machine (VM) running macOS and work from there. Next, you need to get to grips with Swift. This is a programming language developed by Apple. More importantly, it’s primarily what you’ll use alongside Xcode to make iOS apps. Swift has the advantage of being the dominant language for iOS development and it’s not hard to learn as it’s similar to other programming languages. Further, Swift boosts efficient and concise memory management and supports dynamic libraries. Therefore, even if you’re new to Swift as a programming language, it should still be a relatively stress-free process. Step 2: Choose an Application Enabled Platform The next step is to choose an IoT Application Enabled Platform (AEP). An AEP is an environment to build and deploy IoT products and services within. As you likely know, building an IoT platform from scratch can be incredibly difficult and a long process. However, an AEP streamlines the process of implementing IoT into your app. Without one, you need to design, build, test, and maintain each part of the IoT stack, including elements like server and database deployment and maintenance, UX and UI build, third-party connections and APIs, and front-end build and maintenance. Essentially, there are two options when it comes to choosing an AEP. First, you can choose a centralized traditional IoT application-enabled platform like Azure IoT and AWS IoT. Or, you can use a decentralized IoT application-enabled platform that uses peer-to-peer communication. While a traditional AEP benefits from software development kits (SDKs) that provide native support to iOS devices, it has some drawbacks. Firstly, there are security concerns. These use the cloud for data storage. As data passes through, it’s vulnerable to bulk data theft or loss. What’s more, data having to pass through a central server may result in high latency for your iOS IoT app. However, with a decentralized AEP, you circumvent these security and latency concerns, and also have lower running costs. Therefore, we recommend going down this route if you want your iOS IoT app to run as smoothly as possible. Step 3: Code the Front-End and Back-End After choosing your AEP, it’s time to code the front-end and back-end of your IoT app. The way data is presented to a user is just as important as the way it is used. Xcode has an Interface Builder built-in that lets you design user interfaces without having to write any code. However, you can make even better user interfaces with the SwiftUI toolkit. Back-end development in IoT is complex and time-consuming. Thankfully, back-end development can usually be aided or entirely handled by the AEP you have chosen. Moreover, you can avoid back-end development altogether if you use a decentralized AEP solution. This is because back-ends are normally the centralized server application of a centralized AEP system. Whereas, with a P2P or decentralized AEP, you just have the client application (front-end) which connects directly to the IoT application running on the IoT device. Step 4: Utilize Apple Native IoT Frameworks As mentioned earlier, if your app is going to be exclusively for iOS, developing natively can have a ton of benefits. Being able to use Apple’s native IoT frameworks is one of them. Apple has developed a couple of IoT frameworks for use in their devices, so why not use them? HomeKit is an IoT framework that allows users to communicate with and control connected accessories in their homes using your app. It can display, edit, and act upon the data in the home configuration database, and actions can even be activated via Siri. To utilize HomeKit in your project, you enable the HomeKit capability and include the NSHomeKitUsageDescription key in your app’s Info.plist file. This and other frameworks – like HealthKit – can make developing IoT systems for iOS more appealing and easy. Therefore, don’t be afraid to take a quick look over the documentation to see if it would fit into your IoT project. Step 5: Deploy Your App to the App Store The final step is publishing your project. Keep in mind that you need to sign up for the Apple Developer Program to submit your apps for review and eventual publishing. This costs $99 per year. After you sign up, you’ll have access to App Store Connect, where you will be able to see your App analytics and other options. Submit your App and wait around 48 hours for approval. Once this process is over you will have an IoT app for iOS readily available to the public. As you can see, it’s simple to build IoT apps on IoS. Apple’s ease of usability is often cited as a reason for the iPhone’s popularity and, when it comes to developing IoT iOS apps, it’s no different. To make the process even easier, one final suggestion is to employ an IoT platform with finished app templates and demos. This way, developers can experiment with the look and feel of the app — as well as better understand the IoT protocol — before release. If you follow these steps, you’ll be able to build a successful IoT app for Apple’s app store in no time. Good luck.

In the recent ten years, the Internet of Things has shown itself as a breakthrough solution for delivering more informed business strategies, improving customers’ experience, managing assets, automating processes, performing predictive maintenance, and so on. A large role here was played by embedded solutions – hardware and software systems which contribute to the high performance of the whole IoT ecosystem. However, there is no universal method of organizing and deploying the embedded IoT system to guarantee its complete success. On a case-by-case basis, embedded IIoT solutions providers, manufacturers, developers, and business owners have to decide which “things” to equip, how to customize solutions, and how to save without causing harm. However, the future seems to belong to the IoT embedded. As McKinsey reports, by 2030, total revenue for 5G IoT embedded modules will increase more than 50 times! This is partly due to deep learning processors and neural processors contributing to exponential growth in performance and energy efficiency of embedded computing systems. However, to make it real, manufacturers of the ready-made solutions have to study deeply the demand to produce off-the-shelf modules for customers’ specific needs. Despite there being an abundance of ready-made embedded systems on the market today, they are not always in strict adherence to customers' business goals. At some point, the question might arise of reducing the cost of a solution in mass production and of a unique form factor or minimizing the dimensions of the devices. All these factors reinforce the need for custom embedded hardware and software development. This article focuses on the main points to consider while designing an embedded system within IIoT solutions to make it capable of improving business. Embedded Systems for IIoT Solutions: Features and Examples When it comes to IoT development, we technically talk about embedded systems connected to the Internet. Examples of embedded solutions are sensors, actuators, edge devices, application-specific hardware, smart devices, routers, and switches for embedded networking – and certain other equipment can collect data from the environment or produce intelligent reactions of target objects. In theory, any object, from car and cargo to technical staff in the enterprise, can be equipped with sensors. In view of the IoT ecosystem, the main goal here is to ensure the “collaboration” of all the things within, providing non-stop data circulation. A layer of information and communication technology must be added to connect an embedded system to the IoT ecosystem. Like any solution beneficial for business, the IoT ecosystem is created to maximize its performance, which should lead to increased income or decreasing costs for the company. This is what developers should consider from the very beginning. In general, the highly effective nature of embedded systems largely contributed to the global drive of IoT ecosystem deployment on an enterprise scale. Embedded systems can satisfy a business request with the following features: Real-time computing Low power consumption Small size High availability Affordability of development Thus, achieving maximum performance while producing is possible, and exploitation costs are minimal. This allows the building of large and multifunctional embedded systems capable of enhancing the whole IoT ecosystem. However, even such significant benefits can be brought down if the specific system is built according to some template without considering specific needs and trends. Below we describe how these benefits can be maximized. How to Build Embedded Systems Within IIoT Solutions The issue of how to maximize benefits from the embedded systems often comes down to how to properly design the whole IoT ecosystem since all its components are interdependent. Therefore, the development of the embedded systems within the Enterprise Internet of Things (EIoT) has to be strictly coordinated on a high level and aimed to find the optimal design solutions to solve a specific business issue, optimize or automate processes in the enterprise, and improve security. Connect Strategic Design Thinking Think out the architecture carefully. One factor is to prove the system’s workability at the PoC stage. Still another – is to show that a specific system’s configuration and chosen IIoT solutions are the optimal way to increase the effectiveness of the target processes in the enterprise. Since embedded systems are created to interact with the environment, here we have to identify the most effective and cost-effective way of interaction considering all available sensor, network, and processor solutions. Think about the information you need to make decisions, how to collect this information, and with what sensors and tools. For instance, monitoring warehouses can be used with both drones and sensors, which can provide temperature measurements. Consider the decisions to be made on edge and cloud layers and how the devices interact in the system. Consider Possible Expansion of the IoT Ecosystem It frequently happens that after launching the embedded device, it begins to slow down due to insufficient computing power. It forces developers to change the working system by redesigning the architecture or replacing the processor with the more powerful one. It takes additional human and time resources. To achieve higher performance and have more options in connectivity, graphic display, and cloud computing, the best solution is to implement a more powerful controller from the very beginning. Calculate how much memory you need, what calculations you need, and the speed of these calculations. Also, new embedded devices connected can compromise connectivity which creates a gap in real-time data analytics. To prevent this, the company, for instance, can consider mesh networks, which become stronger by adding new devices. Invest in Custom Embedded Software Although the emphasis within embedded systems design is on software development, even complex embedded solutions designed, for instance, for avionics, often have software gaps because of the specifics of embedded programming and testing. Embedded software is not as flexible as the application software is since every code line directly influences hardware. Therefore, if embedded hardware development can be low in cost producing even a single unit, we recommend not to save on custom software and pay special attention to it at the development stage. Although you can find off-the-shelf embedded systems on the market, which include software specialized for particular microcontrollers, ready-made embedded solutions significantly narrow their application area. Consider the Machine Learning Method With Embedded IIoT Solutions By connecting neural network solutions within embedded systems, a company can not only accelerate operations but also save on other system components. For instance, by utilizing machine learning algorithms for visual QA processes in the enterprise, it can save on high-resolution cameras. The greater data that comes, the smarter the system becomes, allowing responsible parties to devote the devices to more responsible tasks. In addition, applying machine learning algorithms within the embedded device eliminates the need to transmit data into the cloud and increases the security level thereby. Follow the Trends in Embedded IoT Development Although the systems themselves are highly efficient, steps are being taken to further reduce power consumption while increasing battery capacity dozens of times. For instance, NB-IoT – is a low-power and wide area network that provides reliable communication between embedded devices. For embedded systems providing vision sensing, there are also some cutting-edge solutions like Etacamera, which is the most energy-effective image capturing system for now. Even embedded computers are becoming more efficient and powerful: the new version of Raspberry Pi significantly exceeds the previous one. Let Your Device Communicate Without the Internet In the multi-layer IoT ecosystem, devices can generally exchange the data locally and transfer it to the cloud. Embedded devices can support various protocols allowing them to communicate without central unit commands. For providing intelligent reactions within edge computing, it would be better to implement internet-free protocols, such as Zigbee or Thread. This makes the system more autonomous and invulnerable to the internet shutdown. Trends of Embedded Systems for IIoT Solutions While the manufacturers are searching for ways to improve the embedded system components, the IoT ecosystem designers and developers are forced to predict possible issues the area might face in the near future. For now, the future looks like this: AI widespread introduction. Today, systems with machine learning implemented are becoming more general. Soon there will be enough experience in using Artificial Intelligence in IoT systems to analyze it on a global scale and outline further development ways. Since today it continues to prove its value in various areas, from factories to medicine; whereas the solutions for AI implementation are becoming more affordable, we can expect the AI-based embedded system for every IoT solution. Growth of wireless connections. Since we expect the internet everywhere in the future, wireless connections should significantly increase in embedded systems. Therefore, despite a large number of wired connections, embedded systems should adapt to the new connectivity era. Increase embedded security solutions. With the exponential growth of IoT devices, there appear to be more points for hacker attacks thereby. Therefore, we can expect the corresponding growth of security solutions within embedded devices. For instance, built-in security silicon from Infineon, Microchip, STMicroelectronics, Micron, Winbond, and others is becoming more frequent in embedded hardware design. Extra speed computing. Most likely, it will take a bit more time for quantum computing to become widespread. But when it happens, the computing power will significantly increase, which will lead to a significant increase in the speed of processors, and the whole system as well. The idea behind IoT ecosystem implementation belongs to investments in the future, and companies don’t expect to see a return on investment immediately. The majority of solutions have the main goal of deep data analysis to make accurate predictions. Therefore, it makes sense to consider these trends embedded to be prepared for the near future. Conclusions Since the goal of embedded systems is to interact with the environment, they need to be designed to perform a particular function, considering low power consumption factors, secure architecture, reliable processors, and so on. To deliver a highly effective embedded IoT ecosystem, a company should consider the following: There are plenty of embedded solutions for IoT on the market. However, to match it with business needs, the company has to invest in customization. Despite embedded systems being low-powered and cost-effective in general, companies should consider them within the whole IoT ecosystem to create optimal architecture solutions. If you suppose that you found the most cost-effective IIoT solutions with the highest performance potential, check out the trends again. Follow the IoT market. New components, devices, and connectivity solutions constantly appear in the market. At any moment, a solution could appear and be considered an ideal match within your IoT ecosystem.

An MQTT topic is a UTF-8 encoded string that is the basis for message routing in the MQTT protocol. A topic is typically leveled and separated with a slash / between the levels. This is similar to URL paths, for example: Plain Text chat/room/1 sensor/10/temperature sensor/+/temperature sensor/# In comparison to topics in other messaging systems, for example, Kafka and Pulsar, MQTT topics are not to be created in advance. The client creates the topic when subscribing or publishing, and does not need to delete the topic. Although allowed, it is usually not recommended to use topics that begin or end with /, such as /chat or chat/. The following is a simple MQTT publish and subscribe flow. If APP 1 subscribes to the sensor/2/temperature topic, it will receive messages from Sensor 2 publishing to this topic. MQTT Wildcards Single-Level Wildcard + (U+002B) is a wildcard character that matches only one topic level. When using a single-level wildcard, the single-level wildcard must occupy an entire level, for example: Plain Text "+" is valid "sensor/+" is valid "sensor/+/temperature" is valid "sensor+" is invalid (does not occupy an entire level) If the client subscribes to the topic sensor/+/temperature, it will receive messages from the following topics: Plain Text sensor/1/temperature sensor/2/temperature ... sensor/n/temperature But it will not match the following topics: Plain Text sensor/temperature sensor/bedroom/1/temperature Multi-Level Wildcard # (U+0023) is a wildcard character that matches any number of levels within a topic. When using a multi-level wildcard, it must occupy an entire level and must be the last character of the topic, for example: Plain Text "#" is valid, matches all topics "sensor/#" is valid "sensor/bedroom#" is invalid (+ or # are only used as a wildcard level) "sensor/#/temperature" is invalid (# must be the last level) Topics Beginning With $ System Topics The topics starting with $SYS/ are system topics mainly used to get metadata about the MQTT broker's running status, statistics, client online/offline events, etc. $SYS/ topic is not defined in MQTT specification, however, most MQTT brokers follow this recommendation. For example, the EMQX supports getting cluster status through the following topics. Topic Description $SYS/brokers EMQX cluster node list $SYS/brokers/${node}/version EMQX Broker version $SYS/brokers/${node}/uptime EMQX Broker startup time $SYS/brokers/${node}/datetime EMQX Broker time $SYS/brokers/${node}/sysdescr EMQX Broker description EMQX also supports rich system topics such as client online/offline events, statistics, system monitoring and alarms. For more details, please see the EMQX System Topics documentation. Shared Subscriptions Shared subscriptions are a feature of MQTT 5.0, a subscription method that achieves load balancing among multiple subscribers. The topic of a shared subscription starts with $share. Although the MQTT protocol added shared subscriptions in 5.0, EMQX has supported shared subscriptions since MQTT 3.1.1. In the following diagram, three subscribers subscribe to the same topic $share/g/topic using a shared subscription method, where the topic is the real topic name they subscribe to, and the publishers publish messages to the topic, but NOT to $share/g/topic. In addition, EMQX also supports the use of the shared subscription prefix $queue in MQTT 3.1.1. It is a special case of a shared subscription, which is equivalent to having all subscribers in one group. For more details about shared subscriptions, please refer to EMQX Shared Subscriptions documentation. Topics in Different Scenarios Smart Home For example, we use sensors to monitor the temperature, humidity and air quality of bedrooms, living rooms and kitchens. We can design the following topics: We can design the following topics: myhome/bedroom/temperature myhome/bedroom/humidity myhome/bedroom/airquality myhome/livingroom/temperature myhome/livingroom/humidity myhome/livingroom/airquality myhome/kitchen/temperature myhome/kitchen/humidity myhome/kitchen/airquality Next, you can subscribe to the myhome/bedroom/+ topic to get temperature, humidity and air quality data for the bedroom, the myhome/+/temperature topic to get temperature data for all three rooms, and the myhome/# topic to get all the data. Charging Piles ocpp/cp/cp001/notify/bootNotificationPublish an online request to this topic when the charging pile is online. ocpp/cp/cp001/notify/startTransactionPublish a charging request to this topic. ocpp/cp/cp001/reply/bootNotificationBefore the charging pile goes online, it needs to subscribe to this topic to receive the online response. ocpp/cp/cp001/reply/startTransactionBefore the charging pile initiates the charging request, it needs to subscribe to this topic to receive the charging request response. Instant Messaging chat/user/${user_id}/inboxOne-to-one chat: Users subscribe to this topic after they are online and will receive messages from their friends. When replying to a friend, just replace the user_id of the topic with the friend's id. chat/group/${group_id}/inboxGroup chat: After the user successfully joins a group, they can subscribe to the topic to get the group's messages. req/user/${user_id}/addAdd a friend: Publish a friend request to this topic (user_id is the friend's id).Receive friend requests: Subscribe to this topic (user_id is the subscriber's id) to receive friend requests from other users. resp/user/${user_id}/addReceive replies to friend requests: Before adding friends, the user needs to subscribe to this topic (user_id is the subscriber's id) to receive the request results.Reply to friend request: Send a message to this topic (user_id is the friend's id) about whether or not to approve the friend request. user/${user_id}/stateUser Status: Subscribe to this topic to get your friends' online status. MQTT Topics FAQ What Is the Maximum Level and Length of an MQTT topic? MQTT topic is UTF-8 encoded strings, and it MUST NOT be more than 65535 bytes. However in practice, using shorter length topic names and fewer levels means less resource consumption. Try not to use more topic levels “just because I can”. For example, my-home/room1/data is a better choice than my/home/room1/data. Is There a Limit to the Number of Topics? Different message servers have different limits on the number of topics. Currently, the default configuration of EMQX has no limit on the number of topics, but the more topics, the more server memory will be used. Given the large number of devices connected to the MQTT Broker, we recommend that a client subscribes to no more than ten topics. Do Wildcard Subscriptions Degrade Performance? When routing messages to wildcard subscriptions, the broker may require more resources than non-wildcard topics. It is a wise choice if the wildcard subscription can be avoided. This very much depends on how the data schema is modeled for the MQTT message payload. For example, if a publisher publishes to device-id/stream1/foo and device-id/stream1/bar and the subscriber needs to subscribe to both, then it may subscribe device-id/stream1/#. A better alternative is perhaps to push the foo and bar part of the namespace down to the payload, so it publishes to only one topic device-id/stream1, and the subscriber just subscribes to this one topic. Can I Subscribe to the Same Topic With a Shared Subscription and a Normal Subscription? Yes, but it is not recommended. Per the MQTT specification, multiple subscriptions will result in multiple (duplicated) message deliveries. What Are the Best Practices for MQTT Topics? Do not use # to subscribe to all topics. The topic should not start or end with /, such as /chat or chat/. Do not use spaces and non-ASCII characters in the topic. Use _ or - to connect words (or camel case) within a topic level. Try to use fewer topic levels. Try to model the message data schema in favor to avoid using wildcard topics. When wildcard is in use, try to move the more unique topic level closer to root. e.g. device/00000001/command/# is a better choice than device/command/00000001/#.

The potential of 6G technology will become evident because of its intrinsic power to allow immersive smartphone experiences. It opens up multiple opportunities that blur boundaries between physical and online platforms. In other words, 6G technologies will create a collision of material and virtual reality. Work and home will be deeply connected, and people will move freely around for social interaction. According to the latest figures, the global 6G market will accomplish a financial worth of about $1.04 billion in 2028. By 2032, the forecast shows that the industry will reach around $40.99 billion, exhibiting a CAGR of 150.4%. 6G Networks: Lack of Protocols but High Market Potential Currently, no standards for 6G networks have been created because there is still work to do regarding their power consumption and wireless signal transmission. The U.S. Federal Communications Commission (FCC) has set 95 GHz and 3 THz for initial Research and Development (R&D). According to the latest research, Finland's University of Oulu initiated the 6Genesis research project to establish a 6G vision for 2030. The institution has decided to cooperate with Japan's Beyond 5G Promotion Consortium regarding Finnish 6G Flagship research on 6G networks. Moreover, South Korea's Electronics and Telecommunications Research Institute (ETRI) is experimenting with the terahertz frequency band for 6G. In contrast, Samsung plans to invest more than $355 billion into chipset manufacturing to facilitate the progress of 6G architecture. 6G Technologies: A Powerful Cluster of Numerous Networks Commercialization of 6G technologies is likely a decade away because there is significant work to do. Experts must ponder the technological challenges of delivering higher speed, more storage capacity, and lower latencies than 5G networks. As 6G networks will trigger the convergence of existing technologies, it will be the network of multiple interfaces. In accordance with Phil Solis, the applications of the 6G network will be beyond marketing because of Orthogonal Frequency-Division Multiple Access (OFDMA) in WiFi 6. It is a technology that supports uplink and downlink communications with several customers with the help of numerous Resource Units (RUs). As per Paolo Gargini, experts are talking about the hybrid applications of 6G technology, but there is infrastructure transformation required. For instance, there will be a need to install fiber broadband connections to limit the loss of signals during data transmissions at Tera-Hertz (THz) frequencies. There is another way to improve data transfer rates and control resource consumption. Japan’s telecommunications company NTT's 6G work comprises the progress and testing of a mobile network that utilizes an end-to-end optical communications architecture called Innovative Optical and Wireless Network (IOWN). The network cluster uses photons for fast data transmissions without transforming data into electrical signals. NTT aims to bring a 100-fold improvement to power use, end-to-end latencies, and transmission capacities compared to traditional approaches. According to Spirent Douglas, 6G technologies will facilitate the convergence of WiFi and cellular technologies. There can be any software underneath the 6G network, but if there is standardized interoperability, users will have no issues. Nevertheless, the visions for 6G and any standardized approaches are highly likely to transform before their widespread commercial use. Potential Applications of 6G Technologies 6G networks will transform the world because of their wide applications. According to the experts, its various use cases are below: In the telecommunication industry, 6G networks will introduce multi-sensory technologies to establish new ways of social connectedness and interact with the environment via all five senses. It means that 6G networks will eradicate physical and time-related limitations through holographic imaging and streamlining human-to-human and human-to-machine connections. Almost all the networks will be AI-driven, facilitating complete digitization. According to Andreas Roessler, TeraHertz communication (THz), Joint Communication and Sensing (JCAS), AI & ML, Reconfigurable Intelligent Surfaces (RIS), and Visible Light Communication (VLC) are among the type of advancements that will transform the 6G era. JCAS will improve communication via efficient beam management, alignment, and feedback. It will enable new applications — for instance, gesture recognition, vulnerable road user detection, and human-machine interaction. 6G networks will comprise ultra-wideband, low latency, high intelligence, and spatialization. Such factors will facilitate better communication and allow immersive Extended Reality (XR), high-fidelity holograms, and digital replicas without any limitations. Consequently, 6G networks will be constructed while keeping in mind the cloud storage to enable efficient reprogramability. A powerful motivation behind 6G networks is the upcoming deployment of Connected Robotics and Autonomous Systems (CRAS), including effective drone delivery, self-driving cars, and autonomous robotics. CRAS mandates control system-driven latency requirements and the potential need for Enhanced Mobile Broadband (EMBB) transmissions of High Definition (HD) maps. CRAS is the top-tier use case that requires stringent standards across the latency spectrum; which is absent in 5G. In accordance with the latest research, identity verification solutions will be extremely important for 6G mesh networking. It implies that the availability of fast data transfers will empower experts to communicate with each other effectively and catch fraud instantly. In this way, it will allow quick local and cross-border communication, enabling law enforcement agencies to conduct efficient criminal investigations. Concluding Remarks The need for massive development and intelligent networks are significant factors behind the growth of the Global 6G Market. According to Polese, the arrival of 6G technology will address the issues of 5G networks. The introduction of 6G with higher frequencies for quick data transfers is highly attractive to universities and industries. As per Jornet, there will be enough progress on 6G to make the advancements evident. Thereupon, it will guide further development and finalization of standards.

With IoT solutions implemented in fleet management, the supervisors and managers will know about the vehicle's health, current position, updates from the drive, fleet health, cargo, and so on. No matter where you are located, the right fleet management structure will make it more proactive and precise. Understanding Fleet Management and the Role of IoT The basic purpose of fleet management is to structure the fleet and its activities to get the best outcome. In terms of management, this includes taking care of the vehicles and drivers, monitoring the vehicle’s health, tracking the cargo, ensuring that the vehicles can deliver the cargo on time, adjusting the vehicle route, and so on. On top of everything, it is about enhancing asset utilization and implementing programs that help with improving the outcome. Generally, fleet managers use a Telematics (combination of telecommunications and information processing) solution to achieve fleet efficiency and optimize operational costs. Managing the fleet is not an easy task, and mistakes often lead to heavy costs. Failure to monitor a vehicle’s health can result in an abrupt or sudden breakdown, which increases the delivery time. And in a supply chain, a delay in one segment can disturb the entire structure. That’s why it is essential to have the right system in place and make it more efficient. One of the ways to get the desired result is to bring the Internet of Things (IoT) into the picture. Role of IoT in Fleet Management IoT-enabled fleet management systems boast sensors, actuators, and firmware to improve operational efficiency and optimize costs while reducing the chances of sudden breakdown and other risks. One of the key roles IoT plays in fleet management is automation, and it digitizes almost everything. It allows existing fleet owners to embrace the digital systems and install them within their operations. With IoT included in fleet management, we will get: Smart vans Smart trucks Smart ships Smart vessels By smart, we do not mean that the vehicles will get artificial intelligence, but with IoT, fleet managers can get access to the vehicle’s location, health, and current standings accurately. With this information, they can make quick and accurate decisions. IoT opens doors to achieve real-time operational efficiency. It can take the fleet managers way above the basic track and trace systems. With the help of sensors, an IoT-enabled system collects data, and the software converts it into readable information. Fleet management can use this spread of information to make quick and accurate decisions. Applications of IoT Fleet Management IoT fleet management allows companies to better coordinate every fleet operation and increase service profitability while reducing costs. According to an Ericsson report, IoT fleet management systems can help reduce fuel consumption costs by 15%. In addition to this, they can also help reduce repair costs and operational costs. Here are some applications of IoT fleet management: 1. Driver Management IoT systems work on installing several cameras and sensors within the vehicle. So, when there are cameras present in and around the truck, the driver will get updates and alerts on different aspects. For instance, the system will help with blind-spot detection and assist them in taking the right turns. It can alert the drivers about the traffic conditions and when to change course without compromising on the timeline. The drivers will also get alerts on when they must take rest and recommend sleep times. All the video generated from inside and outside the cabin is stored on a cloud server and can be used in the future. Advanced IoT systems also have computer vision for monitoring drivers and their behavior. It can send notifications about the driver's health, if their eyes look drowsy, and so on. The real-time updates on the driver’s health allow fleet managers to make quick decisions. 2. Fleet (Vehicle) Maintenance With the smart usage of telematics, fleet managers can monitor vehicles and suggest proactive measures. The proactivity comes in the form of access to the vehicle’s location, assets, and movement authenticated by the sensors and GPS. Some of the things managers will certainly benefit from here includes: Preventive Maintenance: With sensors installed in the vehicles, the fleet managers will receive notifications and warning alerts. This will notify them about the vehicle’s health and whether it needs immediate attention. Parameters like coolant temperature, battery health, engine health, and so on, are always updated in real-time. If there are major problems that might occur due to equipment malfunctioning, the fleet managers can schedule maintenance before the faulty part breaks down in the middle of the road. All this helps with maintaining the vehicle’s overall health and ensures that it works efficiently throughout the lifecycle. Fuel Efficiency: A vehicle’s fuel consumption varies according to the driver’s behavior. Small things like unnecessary idling, decelerating habits, acceleration patterns, breaking patterns, and so on, have an effect on fuel consumption. But with IoT systems added to the vehicle, fleet managers can add all the data and suggest drivers to improve their habits. This ultimately leads to better fuel efficiency. Vehicle Monitoring: Fleet managers and drivers can access complete information about the vehicle with a series of sensors and cameras. The drivers can identify objects, pedestrians, and other vehicles in their way. Access to this sort of detailed information certainly helps the drivers avoid any accidents. The video output from these recordings can be utilized for driver coaching. 3. Cargo Management With the help of telematics, the fleet managers can improve the supply chain and logistics systems. For cargo management, special sensors can be attached inside the vehicle, especially the ones that carry perishable and sensitive cargo. Sensors that check the temperature provide surveillance and detect even the slightest activity can be installed. The vibration sensors can help keep the cargo secure at all times. Furthermore, with the help of cameras, the managers can always keep an eye on what’s going inside and outside of the cargo container. 4. Passenger Information Another form of utility provided by IoT fleet management systems is information about passengers and their load. Plus, due to monitoring expertise, the sensors can detect the number of passengers inside the vehicle and notify the managers about any extra passengers. It can help managers assure that the drivers are following the guidelines, especially after the pandemic. If we take an overview of all these applications of IoT fleet management, it won’t be wrong to say that IoT is making the entire fleet management system more efficient. It allows automating the majority of the tasks and allows micro-managing every aspect leading to better management and assured results. Benefits of a Good Fleet Management System Fleet operators, supervisors, and managers will always have the upper hand with IoT. Lower Fuel Consumption We have already established the fact that how an IoT system leads to better fuel efficiency and lower consumption. IoT-enabled fleet management provides drivers and managers with accurate information. This is about a vehicle's health, driver’s behavior, driving pattern, and road traffic. Based on the information recorded, the IoT software can recommend changes to the driver’s behavior, suggest route changes in real-time, and help with the vehicle's immaculate health via predictive maintenance. Lower Repair Costs With predictive maintenance in the fold, the vehicle won’t go into sudden breakdowns and malfunctions. As the managers will always be aware of the vehicle’s health, they can pre-schedule maintenance activities. This reduces the repair and service costs because you are ahead of time when it comes to changing the vehicle parts. Lower Operational Costs Managing a fleet is not only about maintaining the vehicles. Instead, it involves a lot of related activities, and most of them are dependent on each other. With IoT systems, fleet managers can keep an eye on all of these systems and ensure that they are working accurately. Automation Automation is achieved with IoT fleet management as it helps keep track of everything and takes control of certain tasks. For instance, an IoT management system can send recommendations to the drivers to change the route or stop idling, and so on, based on the information it gathers. In case of a vehicle breakdown, the system can alert the operators and emergency services. Because it already has access to the vehicle’s location, sending the distress signal to the nearby services is easier. Better Visibility Lastly, with IoT fleet management, you will get complete visibility into what is happening with the fleet. The software interface provides information about every vehicle on a single dashboard. You will get notifications and reminders about the vehicle, driver, cargo, route, and so on. This way, you will always know where the vehicle is, what it is carrying, where it is going, in what time it will reach the destination, how much fuel it will spend, and so on. Conclusion IoT in fleet management will bring intelligence and efficiency to the entire cohort of fleet operations. With a tremendous potential to change things for the better within the industry, it is high time that fleet operators adopt the advanced mechanisms provided by IoT to manage and operate their fleets.

MQTT is a lightweight IoT messaging protocol based on publish/subscribe model, which can provide real-time reliable messaging services for connected devices with very little code and bandwidth. It is widely used in industries such as IoT, mobile Internet, smart hardware, Internet of vehicles, and power and energy. Django is an open-source Web framework and one of the more popular Python Web frameworks. This article mainly introduces how to connect, subscribe, unsubscribe, and send and receive messages between MQTT clients and MQTT brokers in the Django project. We will write a simple MQTT client using the paho-MQTT client library. paho-mqtt is a widely used MQTT client library in Python that provides client support for MQTT 5.0, 3.1.1, and 3.1 on Python 2.7 and 3.x. Project Initialization This project uses Python 3.8 for development testing, and the reader can confirm the version of Python with the following command. $ python3 --version Python 3.8.2 Install Django and paho-mqtt using Pip. pip3 install django pip3 install paho-mqtt Create a Django project. django-admin startproject mqtt-test The directory structure after creation is as follows. ├── manage.py └── mqtt_test ├── __init__.py ├── asgi.py ├── settings.py ├── urls.py ├── views.py └── wsgi.py Using Paho-MQTT This article will use free public MQTT Broker provided by EMQ. The service is created based on MQTT Cloud service - EMQX Cloud. The server access information is as follows: Broker: broker.emqx.io TCP Port: 1883 Websocket Port: 8083 Import Paho-MQTT import paho.mqtt.client as mqtt Writing Connection Callback Successful or failed MQTT connections can be handled in this callback function, and this example will subscribe to the django/mqtt topic after a successful connection. def on_connect(mqtt_client, userdata, flags, rc): if rc == 0: print('Connected successfully') mqtt_client.subscribe('django/mqtt') else: print('Bad connection. Code:', rc) Writing Message Callback This function will print the messages received by the django/mqtt topic. def on_message(mqtt_client, userdata, msg): print(f'Received message on topic: {msg.topic} with payload: {msg.payload}') Adding Django Configuration Items Add configuration items for the MQTT broker in settings.py. Readers who have questions about the following configuration items and MQTT-related concepts mentioned in this article can check out the blog The Easiest Guide to Getting Started with MQTT. This example uses anonymous authentication, so the username and password are set to empty. MQTT_SERVER = 'broker.emqx.io' MQTT_PORT = 1883 MQTT_KEEPALIVE = 60 MQTT_USER = '' MQTT_PASSWORD = '' Configuring the MQTT Client client = mqtt.Client() client.on_connect = on_connect client.on_message = on_message client.username_pw_set(settings.MQTT_USER, settings.MQTT_PASSWORD) client.connect( host=settings.MQTT_SERVER, port=settings.MQTT_PORT, keepalive=settings.MQTT_KEEPALIVE ) Creating a Message Publishing API We create a simple POST API to implement MQTT message publishing. In actual applications, the API code may require more complex business logic processing. Add the following code in views.py. import json from django.http import JsonResponse from mqtt_test.mqtt import client as mqtt_client def publish_message(request): request_data = json.loads(request.body) rc, mid = mqtt_client.publish(request_data['topic'], request_data['msg']) return JsonResponse({'code': rc}) Add the following code in urls.py. from django.urls import path from . import views urlpatterns = [ path('publish', views.publish_message, name='publish'), ] Start the MQTT Client Add the following code in __init__.py. from . import mqtt mqtt.client.loop_start() At this point, we have finished writing all the code, and the full code can be found on GitHub. Finally, execute the following command to run the Django project. python3 manage.py runserver When the Django application starts, the MQTT client will connect to the MQTT Broker and subscribe to the topic django/mqtt. Testing Next, we will use an open-source cross-platform MQTT client - MQTT X, to test connection, subscription, and publishing. Test Message Receiving Create an MQTT connection in MQTT X, enter the connection name, leave the other parameters as default, and click the Connect button in the upper right corner to connect to the broker. Publish the message Hello from MQTT X to the django/mqtt topic in the message publishing box at the bottom of MQTT X. The messages sent by MQTT X will be visible in the Django runtime window. Test Message Publishing API Subscribe to the django/mqtt topic in MQTT X. Use Postman to call /publish API: publish the message Hello from Django to the django/mqtt topic. You will see the messages sent by Django in MQTT X. Summary At this point, we have completed the development of the MQTT client using paho-mqtt, enabling communication using MQTT in Django applications. In practice, we can extend the MQTT client to achieve more complex business logic based on business requirements.

This is the second article in the "Managed MQTT Broker Comparison" series. Here is the link to the first article. Brokers I Choose to Compare I choose the products from independent MQTT Broker vendors who focus on this area instead of other IoT fields. Compared to the comprehensive IoT platform like AWS IoT Core or Azure IoT Hub, the independent products are more flexible and avoid binding with particular cloud services. Managed MQTT Brokers are usually the cloud implement of self-hosted MQTT Broker. In this article, I’ll compare the console and dashboard features. For the product package, I choose the relatively low tier of each product which are affordable for personal or small business. By the time I wrote this article, the standard version of HiveMQ Cloud was not available anymore, so I chose the GSYG Mode instead. Cloud Service and Regions CloudMQTT is absolutely the winner, supporting up to 59 regions. In EMQX Cloud, 17 regions are available. The cloud provider of Cedalo is Hetzner, and servers are located in Virginia, U.S; Finland; and two locations in Germany. AWS or Azure can be chosen for cluster creation, but the region is assigned automatically. Connectivity The most important function of the console is to indicate the address and port for MQTT brokers and guide the user to quickly complete the connection. EMQX Cloud EMQX Cloud offers two MQTT ports: 15445(MQTT) and 15505(MQTT). The port is dynamic in Standard Plan. You can test the connection easily through “Online Test“ by setting up a WebSocket client. HiveMQ Cloud HiveMQ Cloud offers standard TLS ports, 8883(MQTT) and 8884(Websocket). Cedalo — Pro Edition Same as HiveMQ, Cedalo Pro Edition provides TLS over MQTT and WebSocket. CloudMQTT CloudMQTT supports both the 1883 port and the 8883 port. Like EMQX Cloud, it’s easy to test the connection by sending a message from WebSocket UI in the console. Comparison of Connectivity Authentication and Access Control Authentication is typically used to define usernames and passwords for clients' verification, while access control can define client Pub/Sub under certain conditions. EMQX Cloud The device credentials rely on username and password authentication in EMQX Cloud. Set username and password in the console or upload a CSV file that contains all the authentication information to the console. The device uses a pair of usernames and password to sign in. The ACL(Access Control) allows for rules definition over “Client ID, “Username, “ and “All Users. “ For example, I can set a rule that only allows a client (mqttx_07cb8109) to publish and subscribe to the topic “light_control/test. “ The way to set the rules is straight and flexible. In addition to the normal way of setting up authentication and access control, EMQX Cloud allows you to forward authentication from your database. There are five ways to fetch data: HTTP auth, MySQL, PostgreSQL, Redis, and JWT auth. HiveMQ Cloud The Access Management section of HiveMQ Cloud is quite simple. To set up the username and password, one needs to add the credentials one by one, which is not convenient for large-scale import. And there is no access control over topics. Cedalo — Pro Edition In Cedalo, you need to define a client first and then add a role to this client. In order to control access, rules can be applied to a certain role. It's not so straightforward but can do the job. CloudMQTT In CloudMQTT, batch import is not available. The ACL rules can be set globally or individually to the username. The way to define a rule is to use wildcard characters which is a little bit tricky. Comparison of Auth Metrics and Statistics EMQX Cloud EMQX Cloud provides four incremental metrics: messages, clients, packets, and delivery. You can view the display chart corresponding to each indicator and the detailed information at a certain point in time. EMQX Cloud provides monitoring metrics to view data such as TPS, number of connections, subscriptions, and topics in real-time. Clients card list all the clients that connect to the broker at the moment. Subscriptions card list all the topics the broker subscribed to. HiveMQ Cloud All the Metrics and Statistics are available in HiveMQ Control Center. However, Control Center is not included in Pay As You Mode. If you want to know more about this function, check the documents for more information. CloudMQTT In Metrics, the top graph group shows the server metrics on CPU, Memory, Disk, and Network. The bottom graph group shows the clients' connections and messages. The statistics page displays the systematic parameters directly. There are 27 statistics indicating various aspects of deployments. It will be much better to visualize all the indicators. Comparison of Metrics and Statistics Integration EMQX Cloud In Standard Plan, you can create an MQTT bridge to forward the messages to another broker or send the messages to the web application by Webhook. CloudMQTT Broker bridge is used to send messages to another broker or receive messages from another broker. CloudMQTT integrates the ability to send messages to Amazon Kinesis Stream. Billings EMQX Cloud On the Billing page, you can find both brief and detailed information about every cent spent. HiveMQ Cloud CloudMQTT Logs and Notification EMQX Cloud Logs offer the ability to search for keywords, providing multiple levels of log information, including ClientID, ClientIP, Username, Topic, Resource, and Rule ID, as well as filtering by error types. EMQX Cloud provides complete alerts reminders and alert integration, allowing users to make corresponding treatments promptly based on the alerts. EMQX Cloud provides the following alerts: Email, PageDuty, and Webhook (link the alerts to your system through webhook or to Slack group). CloudMQTT The Server Log Page lists all the logs, and the debug mode is quite useful for error detection. The notification can be sent by several options: Email, Webhook, PageDuty, OpsGenie, VictorOps, and Slack when an alarm is triggered. Besides MQTT-related alarms, the hardware alarms about CPU, memory, and disk are detected as well. Comparison of Logs and Notifications Conclusion EMQX Cloud The EMQX Cloud console features are the most comprehensive, providing everything needed for MQTT Broker-based IoT applications. It’s designed for real IoT application scenarios more than MQTT learning and testing. Although the price is relatively high, the monthly usage cost will be around $100 if the package is prepaid annually. EMQX Cloud also provides excellent technical support service through the ticket system, and the replies are on time. HiveMQ Cloud Most of the features of HiveMQ Cloud, except those related to connectivity and access management, are in the Control Center, which is only available in the Standard and Dedicated versions. (For some reason, it is no longer possible to create the Standard version, so it’s not so easy for most users to experience the advanced features). In the Pay As You Go version, the functionality is pretty poor. If your application scenario is simple and the traffic and devices are limited, you can choose PSYG to reduce the cost. However, it is not recommended for users with higher functional requirements. Cedalo — Pro Edition Probably because of the trial version, the experience of using Cedalo's MQTT Broker is poor. It's more like a Beta in progress instead of a commercial product. There is no comprehensive statistics and monitoring, lack of notification method, billing function, and so on. In comparison with other products, it does not show any impressive advantages. CloudMQTT As you can see from the comparison, CloudMQTT’s console features are comprehensive and promise a mature product. In terms of comprehensiveness, CloudMQTT ranks only second to EMQX Cloud in managed broker comparison. The 100-connection version is insufficient for large use. And the next upgrade (1000 connection version) price will be $95 per month. The price is quite reasonable and competitive for all the features.

This is the third article in the "Managed MQTT Broker Comparison" series. Link to the previous articles in the series: Managed MQTT Broker Comparison - Product Packages and Pricing Managed MQTT Broker Comparison - Console / Dashboard Features Performance Test According to the comparison in previous articles, I select EMQX Cloud and Cloud MQTT. The specification is the Standard Plan of EMQX Cloud with 1000 connections and CloudMQTT Loud Leopard with 1000 connections. The bench software I choose – XMeter. XMeter is a fully managed MQTT load testing service based on Jmeter. There are three testing scenarios that can be set easily. EMQX Cloud Performance Test The dashboard is very comprehensive for monitoring all aspects of the connection. You can easily get understand the connection situation in current. Publish Mode The cloud broker receives 1000 messages per second and sends zero because there are no subscriber connections. Performance Metrics in XMeter, the details can be found here. One-to-One Mode The broker receives 500 messages per second and sends 500 messages per second on balance. Performance Metrics in XMeter, the details can be found here. Subscribe Mode The broker receives one message per second from only one publisher and sends 1000 messages to 1000 subscribers per second. Performance Metrics in XMeter, the details can be found here. Test Scenarios on Metrics From the metrics dashboard, the moment of client connections and client disconnections. Meanwhile, the message received, the message sent, and the message dropped correspondingly. CloudMQTT Performance Test There is no real-time indicator of connections in the CloudMQTT Dashboard. We can find the clients and messages in MQTT metrics in the long-term chart. Publish Mode Performance Metrics in XMeter, the details can be found here. One-to-One Mode Performance Metrics in XMeter, the details can be found here. Subscribe Mode Performance Metrics in XMeter, the details can be found here. Test Scenarios on Metrics Comparison of the Performance Both EMQX Cloud broker and Cloud MQTT broker have a good performance from the connection test. In one-to-one mode, Latency is quite observable in CloudMQTT. However, the response success rate is promised. Integration Capability “Integration“ means sending messages to other services or systems from MQTT Broker, which in most architecture designs, is a messaging middleware for collecting and delivering. Integration capability is essential to build a whole system with a messaging broker as middleware. EMQX Cloud The integration capabilities are different between the Standard Plan and the Professional Plan. In the Standard Plan, data can be forwarded to the developer's web service via the rules engine and bridged to other MQTT Brokers, while in the Professional Plan, the options are more diverse. In addition to the features supported in the Standard Plan, data can be forwarded to 30+ data services like message queues or databases in the Professional Plan. HiveMQ Cloud It’s introduced that HiveMQ Enterprise Extension for Kafka can be enabled in the Dedicated version. Cedalo — ProEdition No data integration yet. CloudMQTT CloudMQTT provides two data integration capabilities. A bridge can forward messages to another broker or AWS Kenisis, which is available for the dedicated instance. API EMQX Cloud Developers can manage authentication, access control, clients, subscription, topics, messages, and metrics through the APIs. With all these interfaces, you can develop a comprehensive cloud MQTT management application that will be well integrated with other systems. HiveMQ Cloud Backup, trace, and client information are available through the API. It’s impossible to develop a whole mirror system because of the limited fields. Cedalo — ProEdition No API provided yet. CloudMQTT It provides the API for authentication and instance management, lacking the capability for querying the clients' information. Documentation and SDKs EMQX Cloud The structure of the documentation is clearly designed. The team detailed the key factors and essential concepts for developers. The content of the documentation is script translated from its Chinese pages with some terminology or syntax issues. SDK Languages: Python, Go, Java, Nodejs, C, C#. HiveMQ Cloud The documentation of HiveMQ Cloud is mixed with other products instead of being presented alone. It’s a bit confusing whether the feature is or is not exclusive to the cloud because the documents are shared. SDK Languages: Java, Python, Javascript, Go, C, Dart. Cedalo — ProEdition The documentation is thorough and includes an introduction to the basics of the MQTT, making it very friendly for developers who are new to MQTT. SDK Languages: Not found. CloudMQTT Several major features are introduced, but the content is not too comprehensive enough. SDK Languages: Ruby, Python, Nodejs, Java, Go, .Net, PHP. Community and Event EMQX Cloud EMQX owns 10.5 stars on Github, indicating a fairly active community. In addition to the open-source project, there are video presentations of key features and Webinar clips on the Youtube channel. HiveMQ Cloud Developers can post questions or issues on the HiveMQ community site and get answers from the team in time. The Youtube channel is also rich in content, including MQTT essentials to help beginners quickly on board and regular Webinars to bring developers the latest news. Cedalo — ProEdition You can get help by submitting questions in the forum. CloudMQTT No community or event-related content was found on the website. Comparison of the Development Capabilities and Community Congratulations to EMQX for winning the most medals in development capabilities and community.