To gather insights on the evolution of IoT to this point in 2017, we spoke to 19 executives who are familiar with the current state of the Internet of Things. 

We asked them, "What real-world problems are being solved by IoT?" Here's what they told us:

• 1) Intellicore is a sports management platform for Formula E racing. Sensor-enabled vehicles with information about what’s happening in the vehicles. Talking to the Tour de France about doing the same thing on bicycles. Time-series data captured with IoT sensors. 2) Smart meters in the UK. Ten million meters as SaaS platforms with the smart meters managed by different utilities saving a lot of money versus having meter readers.
• USPS tracking trucks and postal workers against the weather, traffic patterns enabling them to make decisions in real-time. Add value with data for fleet management, social news, sentiment analysis, stock ticker. Make stock trading decisions based on real-time 360-degree view of the customer.
• Broadband chips are built with custom deliveries for different customers with custom firmware. This results in a complex test matrix. It’s a highly competitive and rapid product cycle. Lots of challenges and ways for things to happen. Exposure is very high.
• Asset management in any industry – computers, mobile devices, trucks. Understanding consumer behavior – how a customer is using the products. I know one company tracking how frequently and how much dog food is used for each serving so they can deliver dog food just in time. There are sensors in farm equipment to know when farmers are plowing, watering, and harvesting.
• 1) Grocer has IoT devices on all in-store freezers to gauge temperature in real-time. If the temperature changes, is this due to more traffic, too much inventory in the freezer, or is the unit about to go down. Prescriptive analytics identifies the root cause so you know what action to take. 2) New technology collect loyalty information from Mac addresses and car keys. Feed into the platform and look at loyal customer behavior, basket analysis and behavioral approaches. Use non-loyalty data to identify shrinkage, robbery, and organized retail crime. Once you have the loyalty information you need to change the paradigm to deliver personalized messages in a non-frightening way. 3) Walgreens is improving the CX and reducing shrinkage with: 1) self-serve analytics, 2) pushed to users, 3) who are told what action to take, 4) the action is tracked to completion, 5) quantified, and 6) faster resolution and learn what you don’t know. Some stores were set up so that it was very difficult for vitamins to be stocked. There was a keystroke error causing an inventory overstock for some stores. Using prescriptive analytics to work “simpler, better, faster.”
• 1) Shipping company needs visibility into delays in shipping, customs, unloading, and delivery. Leverage open source for smarter contacts (sensors) on the ship and the containers. 2) Utilities have a smart grid and can stream telemetry data and APIs to improve outcomes for the utility and the end-user customer. 3) Telcos are enabling IoT infrastructure managed services providing precise GPS for mining and tracking and tracing for shipping.
• 1) Renault self-driving cars are sending all data back to a corporate scalable data repository. 2) French railway is using drones to check lines to determine if they need to be serviced by sending streaming video back to the data repository. 3) A manufacturer is using industrial IoT data to be the new platform of all industrial equipment. 4) Surveillance body camera footage for UK and middle east police forces is being sent back to a data repository.
• First is the transformation from shipping a device to shipping a device with software. 1) We have a bank ATM client reducing the amount of hardware they ship and differentiating based on the software in the machine. We’re seeing the same transactions across different industries using different software in different ways to provide different forms of monetization. 2) Helping PolySync scale to meet increased demand, automate software delivery and updates enabling product differentiation to pursue new market opportunities.
• Connected home to smart home appliances connecting data with the end use of the appliance with mobile or web devices. Enabling different user relationships with different devices like auto refills and who can turn on the oven versus setting an alarm when the cookies are baked. Allow interaction with Alexa and CPG companies. Keeping user and device data so they meet GDPR standards – tracked and auditable consent.
• 1) The oil and gas industry is increasing efficiency of well production by monitoring heat and vibration in the well. 2) A semiconductor chip manufacturer is using yield analytics to identify quality issues and root causes saving $10’s of millions every month. 3) A healthcare equipment manufacturer is improving efficiency and uptime of their devices where more use of the machine generates more billings for their client. 4) Connected car data perspective is challenging since you’re getting a gigabyte of data from every vehicle every second summarized, filtered, and acted on in real-time. Able to make decisions on board in the vehicle. Also, using for fleet management to monitor maintenance and durability. Insurers are tapping into the stream to provide “pay as you drive” offerings. These are mission critical, high requirement applications. 5) Healthcare using EMRs as data stream with updates from IoT devices form the backbone of the healthcare process and a way to connect all the patient’s information to make real-time decisions and recommendations.
• Connected operation services. Collect data to get more operational intelligence. More interest in analytics from descriptive to prescriptive. Start to investigate prescriptive. Monitoring and service helps to improve products and deliver smart connected products.
• Integration between IoT devices and web apps on the cloud. Data from devices in the cloud. Integrating IoT devices from trains to hubs and data from hubs to applications.
• Smart credit cards reduce fraud when the card is not present with a one-time password identifier.
• A good example of an IoT application solving real world problems is our Senior Lifestyle System. The system is designed to help seniors feel safe and live independently at home. Using a network of four or more small sensors in the home, this system is able to securely monitor what is going on in the house—who is moving around, when and where. It learns the normal behavior patterns. The data gathered from the sensors is transmitted to the cloud application via a home gateway, it is analyzed and compared to an established baseline and standard range of deviation, to determine if the resident’s activities fall within “normal” range. If they do not, the system alerts a caregiver or family member. The system does not require cameras or microphones, so there is no undue infringement on privacy. The system is also smart enough to recognize gradual changes over a long period of time that could indicate developing medical problems.
• 1) Warranty customer is collecting data on smart appliances in home, make and model, heuristics and fingerprinting to get warranty information of all of the devices so they can reach out when a warranty is about to expire to sell extended warranties. 2) A student bus company is preparing to use motion and video analytics with counters based on body heat to count students entering and exiting the bus to ensure students are not left on the bus overnight in the depot.
• A great example is a telematics company we are working with that has created a GPS vehicle tracking and fleet tracking solution with more than 3.2 million subscribers. They are using Birst as an analytic product that monetizes their GPS data. With this new data product, they serve three markets: 1) Transportation and logistics - the analytics product helps fleet management companies manage fleet/truck utilization and reduce costly truck idle times; 2) Insurance - device usage data and analytics around that helps insurance providers underwrite premiums based on usage, not driving records; and, 3) Auto dealers - location data helps auto dealers protect their assets and detect fraud.

What are some interesting problems you've seen being solved with IoT?

And in case you're wondering, here’s who we talked to:

• Scott Hanson, Founder, and CTO, Ambiq Micro
• Adam Wray, CEO and Peter Coppola, SVP, Product Marketing, Basho
• Farnaz Erfan, Senior Director, Product Marketing, Birst
• Shahin Pirooz, CTO, Data Endure
• Anders Wallgren, CTO, Electric Cloud
• Eric Free, S.V.P. Strategic Growth, Flexera
• Brad Bush, Partner, Fortium Partners
• Marisa Sires Wang, Vice President of Product, Gigya
• Tony Paine, Kepware Platform President at PTC, Kepware
• Eric Mizell, Vice President Global Engineering, Kinetica
• Crystal Valentine, PhD, V.P. Technology Strategy and Jack Norris, S.V.P., Database Strategy and Applications, MapR
• Pratibha Salwan, S.V.P. Digital Services Americas, NIIT Technologies
• Guy Yehaiv, CEO, Profitect
• Cees Links, general manager Wireless Connectivity, Qorvo
• Paul Turner, CMO, Scality
• Harsh Upreti, Product Marketing Manager, API, SmartBear
• Rajeev Kozhikkuttuthodi, Vice President of Product Management, TIBCO