DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Refcards Trend Reports
Events Video Library
Over 2 million developers have joined DZone. Join Today! Thanks for visiting DZone today,
Edit Profile Manage Email Subscriptions Moderation Admin Console How to Post to DZone Article Submission Guidelines
View Profile
Sign Out
Refcards
Trend Reports
Events
View Events Video Library
Zones
Culture and Methodologies Agile Career Development Methodologies Team Management
Data Engineering AI/ML Big Data Data Databases IoT
Software Design and Architecture Cloud Architecture Containers Integration Microservices Performance Security
Coding Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

Integrating PostgreSQL Databases with ANF: Join this workshop to learn how to create a PostgreSQL server using Instaclustr’s managed service

Mobile Database Essentials: Assess data needs, storage requirements, and more when leveraging databases for cloud and edge applications.

Monitoring and Observability for LLMs: Datadog and Google Cloud discuss how to achieve optimal AI model performance.

Automated Testing: The latest on architecture, TDD, and the benefits of AI and low-code tools.

Related

  • Top 7 Trends in IoT to Look Out for in 2021
  • Top 11 Cloud Platforms for Internet of Things (IoT)
  • How the Internet of Things (IoT) Is Creating Smart Cities
  • PHP Development in the Era of the Internet of Things (IoT)

Trending

  • Vector Database: A Beginner's Guide
  • The Promise of Personal Data for Better Living
  • Understanding Git
  • Snowflake vs. Data Bricks: Compete To Create the Best Cloud Data Platform
  1. DZone
  2. Data Engineering
  3. Big Data
  4. The Key Values of the Internet of Things

The Key Values of the Internet of Things

We recapped some of the most common performance challenges you might face in IoT, and how to tackle them.

Saba Anees user avatar by
Saba Anees
·
Apr. 29, 16 · Opinion
Like (4)
Save
Tweet
Share
6.77K Views

Join the DZone community and get the full member experience.

Join For Free

A few weeks ago I talked about the criteria your team needs to assess before moving forward with adopting into the Internet of Things (IoT) for enterprise. There is definitely no shortage of resources when it comes to accessing the Internet of Things in the market. In fact, the venture capital funding for IoT startups totaled $7.4 billion over six years. However, that does not mean creating an IoT business is easy–your company needs to overcome multiple hurdles in order to create successful IoT devices. We recapped some of the most common challenges you might face in IoT, and how to tackle them. 

1. Devices

The challenges within the Internet of Things go beyond making devices that work; both product and service need to work seamlessly, almost invisibly to an end user. This is true for both the IoT and the consumer side. The service needs to meet needs, easily integrate into daily life or the industrial process, and has to enhance the user’s life or the business process. That means IoT solutions can’t focus simply on reliable hardware; the software backends need to be reliable as well. Consumers expect both their device and its website or app to function 24/7. When devices control real world environments, they cannot simply shut down due to a software bug, as some users experienced with the Nest thermostat. For industrial applications, the consequences of a device shutdown are far more severe than sleeping under an extra blanket. Security poses another challenge. There have already been worms targeting connected devices, such as security cameras; researchers demonstrated they could take over a driverless car. Security experts expect “machine to machine” attacks to increase during 2016. In fact, the risks are so real that the FBI issued a public service announcement to alert companies and the public to the dangers.

Companies also need to develop a strategy to cope with all the data collected by IoT devices. The volume of data is enormous; a jet engine generates 1TB of data every flight. Companies will need to cope with the massive amounts of data, combine data from multiple sources, and run efficient analytic processes. Finding ways to work with it may require adopting new techniques, like edge/fog computing, to reduce the amount of data sent to the backend systems.

2. Process

To build a level of software required by an IoT business model—with high capabilities of availability, security and performance—companies need to bring in skills they may not have needed when developing other products — embedded programming, real-time event processing, big data analytics. Before bringing that level of skill sets, it is important to think about the IoT product’s value to the user, it has to remove friction and perform a practical and useful service. For your product to succeed, the focus must return to the end user. You also need to be careful about committing to specific technologies. It is still early for many IoT standards, so expect to change your architecture as the technology evolves. There are multiple choices for almost every component of an IoT device — different chip vendors, various communication protocols, numerous backend software platforms. Future developments in sensors and batteries may someday let you implement additional functionality that isn’t possible right now. You may also need to adapt in order to scale your device and backend applications to larger volumes of data.

3. End Users

The primary challenge of the IoT device is that its design has to be customer-centric. End users won’t implement technology just for the sake of technology; the hype only goes so far to generate buzz. To achieve market loyalty, the technology must be able to simplify.  The devices also need to mesh with societal expectations. For example, the insurance issues around self-driving cars, including concerns such as the extent of the manufacturer’s liability, aren’t settled. Some insurers may want to adjust underwriting based on data about driving habits gathered by sensors in vehicles. This kind of usage of data raises privacy concerns the public may not be comfortable with.

Building an Ecosystem 

Your IoT offering requires more than just a fancy hardware device. It needs to be part of an ecosystem in which the hardware is just one element. The ecosystem needs to include features for end users. This means a website or smartphone app where they can adjust device configuration settings and monitor device activity since things typically have neither displays nor input mechanisms to interface with. 

The ecosystem needs to include features for third-party developers, to encourage its adoption by allowing others to create add-ons. This means creating APIs and tools for developers to use and implementing a process by which you can test their creations for safety before offering them for download in an online store.

Finally, the ecosystem needs to include features for your own developers. They need tools to monitor the usage of your product “in the wild” to keep an eye on performance and identify issues. Performance testing not only needs to make sure your production environment will handle the volume of messages received but also how your system operates if the connection fails and messages are not received. Your ecosystem also should provide a way to automatically deploy bug fixes and firmware updates to your products.

Outweighing the Challenges 

There are inevitable complexities when it comes to creating and maintaining a consistent IoT product and software. With those challenges, however, come more opportunities for innovation and revenue. There are three main opportunities for companies to implement IoT business models:

  1. Digitize current processes or services: Tasks that are currently performed manually can be automated. For example, remote patient monitoring lets patients transmit vital signs to their doctors’ offices automatically, eliminating the need for follow-up visits.
  2. New business models: For some firms, using IoT devices can mean changing their business model. The World Economic Forum predicts a new “outcome economy” in which sensors will enable companies to charge for usage and guaranteed quality levels. Rolls-Royce, for example, charges per engine flying hour for its TotalCare aerospace service.
  3. Enhancing customer experience: Customers benefit from the always-connected aspect of IoT devices and being able to look at their data themselves. Companies can also take advantage of the data collected from the sensors to understand how customers use their devices and identify opportunities for new features and services that will make customers even happier in the future.

Your IoT offering requires more than just fancy hardware. It needs to be part of an ecosystem in which the hardware is just one element. The ecosystem needs to include features for end users and developers. Sometimes it means providing a front-end application for users to adjust device configuration settings and monitor device activity. Third-party developers must be encouraged to adopt by allowing them to create APIs and implementing a process by which you can test their creations before offering them for download in an online store. 

Finally, the ecosystem needs to include features for your own developers. They need tools to monitor the usage of your product “in the wild” to keep an eye on performance and identify issues. Performance testing not only needs to make sure your production environment will handle the volume of messages received but also how your system operates if the connection fails and messages are not received. Your ecosystem, if built correctly, must provide a way to automatically deploy bug fixes and firmware updates to your products to ensure application and device performance is always providing the ideal experience to both developers and end users. 

Get more out of the Internet of Things, and read the full eBook, Breaking Down the Internet of Things here.

IoT Internet (web browser) Big data

Published at DZone with permission of Saba Anees, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • Top 7 Trends in IoT to Look Out for in 2021
  • Top 11 Cloud Platforms for Internet of Things (IoT)
  • How the Internet of Things (IoT) Is Creating Smart Cities
  • PHP Development in the Era of the Internet of Things (IoT)

Comments

Partner Resources

X

ABOUT US

  • About DZone
  • Send feedback
  • Careers
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 100
  • Nashville, TN 37211
  • support@dzone.com

Let's be friends: