IoT Use Cases

To gather insights on the current and future state of IoT, we talked to 23 executives involved with IoT. We asked them, "What are real-world problems you, or your clients, are solving with IoT?"

Industry Use Cases

• Oil and gas customers are able to optimize placement of drill heads in real-time to optimize output of the well thereby increasing productivity and revenue.
• Manufacturing 4.0 where Qualcomm is measuring factory floor conditions to optimize yield management of chip production.
• Automotive embedded technology in cars to transmit data in intervals, as well as the technology for autonomous vehicles. 
• Autonomous vehicles – how to drive, insight on better routes with less risk and greater safety.
• Phillips is using IoT in MRI machines so they are informed when the machines need to be tuned. They are also aggregating MRI images and analyzing with ML for disease detection.
• Healthcare – provide direct connection to equipment (MRIs) and use AI for the initial triage to diagnose problems and reduce the requirement of putting someone on site by 40% thereby reducing response time, improving customer satisfaction. Connect to the knowledge base for triage.
• Healthcare companies are streaming EMR data and using ML to predict health of patients that are potential for code blue or sepsis shock and send a nurse to visit.
• The U.S. Postal Service captures and tracks all vehicles and personnel for decision and route optimization.
• Utilities have smart meters which enable the analysis of data. PG&E tracks all pipes and information with regards to geolocation and time. Space and time are core differentiators.
• Energy – efficiency of oil well production and where to drill/invest.
• Spiio deploys green wall technology with sensors every 10 square feet that last ten years and collect data every 15 minutes of ambient light, temperature, the moisture content of the soil, and several other variables.
• Aqua Core smart buildings monitoring HVAC, lighting, elevators. As lighting moves to LED new controls and telemetry to measure power draw and monitor for maintenance/ replacement.
• Farming uses extreme distribution of sensors to a waypoint to the internet to the data center.
• Power generation company uses local command and control with availability at the corporate site. Collect data at individual sites, Downsample data back to HQ for trend analysis and a macro view.
• Telecom provider has digital touchpoints into customers. Has 700,000 unfulfilled service requests to connect unconnected devices. Use crowdsource marketplace of freelancers putting Uber-like platform in place increasing customer satisfaction and an additional revenue stream. Addressed the needs of the client base.
• Autonomous lawn mowers, floor cleaners, Nest thermostats, Bigbelly smart city solutions, and John Deere. Intellect at the edge with an understanding of how to bring all of the plumbing together.
• Connected cars, industrial automation, medical devices, smart TVs.
• Connected weather network in Houston monitored the 66 inches of rain that fell during hurricane Harvey and also found that the wind never blew harder than 43 miles per hour so no homes were able to make insurance claims for excessive wind damage. Monitored hailstorm in Denver that caused $1.4 billion in damage with 4,200 hailstones with an average size of 2.5 inches. Able to feed this data into the algorithm to see where the damage occurred, send out adjusters, and uncover fraud. Understory is able to save insurance companies 15 to 30% per storm. We help agriculture increase crop yields. Provide real-time weather alerts including temperature and wind data to support energy and utility companies.
• Supply chains – all products, palettes, containers, and transportation has geolocation streams letting you know where everything is so the supply chain can be optimized, late arrivals can be predicted, replenished and allocated.

Problem/Solution

• Preventive and predictive maintenance so you can take machines down as needed rather than shutting the entire plant down.
• Stream and analyze data in real-time.
• Able to bring voice to the edge for teams in healthcare, construction, firefighters, EMTs, education, and retail. Multi-lingual for healthcare and education.
• CPG – consumables are able to be used and replaced on the right schedule. Smart connected version reports to the app when it’s time to replace and complete the transaction. Connectivity and self-awareness in smaller form factors.
• Our clients are able to be predictive where real-time data can be analyzed to determine when a large piece of machinery or equipment will break down, for example, preventing the failure. Also, prescriptive, intelligent sensors can suggest immediate action at the edges of the organization, for example, thus avoiding outages and even disasters. And finally, adaptive and autonomous, continuous data feeds from sensors can enable systems to learn the right actions to take autonomously.
• Bring clean air to people wherever they go.
• Reduce the manufacturing costs of medical devices, headsets (telco), and automotive. Monetize the use of devices across industries in software like bursts of data within the cloud environment. Help change the business model from a one-time fee to a subscription model. Work with IoT companies to ensure Open Source on IoT devices is in compliance while fixing any security vulnerabilities.
• Industrial asset monitoring with OEMs shifting from selling hardware to selling use/access. In automotive we work with Volkswagen’s connected cars. We’re doing mobile asset logistics and tracking to know where vehicles and shipments are as well as how the vehicle is behaving. We’re involved with low power, wide area networks with cheaper endpoints and long-term battery life in oil and gas and agriculture. We’re also working with insurance companies to help them provide usage-based insurance (UBI) model, where risk evaluations are made based on data generated from real-world driving behavior.
• There are disparate systems that need to be unified into one platform. We are also tackling the following problems: 1) Improving Physical Security: Imagine a world where a man in a ski mask outside of a bank couldn’t even get through the door because the camera identified the activity as suspicious and consequently told the doors to lock, the alarms to sound and the police to come. That is the level of increased security that our AI-driven, video-centric IoT technology can provide – the ability to assess a security threat, act on it, and ultimately prevent crime. 2) Business Optimization: Imagine shopping at a store where no checkout is required so that you never have to wait in line. You simply walk in, take the products you want, and walk out. This was the vision Amazon had in 2017 when they launched the beta version of Amazon Go, a grocery store powered by their Just Walk Out Technology – a combination of computer vision, deep learning algorithms, and sensor fusion that would allow customers to be identified and charged conveniently behind the scenes. There are multiple applications in cloud-ready industries including smart city, smart building, and retail.
• We are helping companies provide healthy drinks to their employees for less money, with less hassle.
• On the consumer side – wearables like clothing and shoes. Consumer health devices. Digital appliance connections. Heavy medical assets/devices like lab diagnostics, MRI – maintenance, supply chain, and parts. Transportation – fleet management containers.
• IoT devices – which have virtually no security and function as web-connected computers – are being shipped by the billions to an unsuspecting public. Even were the public to be aware of such dangers, there is no practical way, using today’s security technologies, to protect these devices, their owners, and others from the damage they can do. Even if the AV market offered some type of security software for these devices (which it doesn’t), the devices don’t have the resources or even a UI for implementing such a client. Furthermore, as described above, the problem is the current security world is fighting using weapons from the last war, while hackers and state-sponsored entities are using a new generation of weapons, including AI/ML and data science. We propose fighting the war taking place today with the latest generation of weapons. This means the use of “agentless” device discovery and profiling, combined with AI-based behavioral anomaly detection that proactively identifies and predicts compromised devices, threats, and risks.
• Predictive and preventive maintenance for oil and gas IoT data platforms from oil rigs to learn of potential failure and plan replacement of parts. Same thing in network electronics for warranty plan replacement parts at depots close to customers.
• Providing edge computing to oil and gas for predictive analytics to improve production. Assisting military and defense with unmanned vehicles – land, air, and sea. Precision agriculture with driverless John Deere tractors maximizing farm utilization and production.

Here’s who we spoke to:

• Adam Fingerman, CXO and Co-founder, and Troy Petersen, Marketing Director, ArcTouch
• Andreas Pettersson, CTO and CPO, Arcules
• Sean Grundy, CEO and Founder, Bevi
• Jeff Bonnell, V.P. of Industry Solutions, Coresystems
• Eli Feldman, CTO, Advanced Technology, EPAM
• Brent Pietrzak, V.P. Producer Solutions and Strategy, Flexera
• Scott Allen, CMO, FreeWave
• Mark Herring, CMO, Tim Hall, V.P. of Products, Brian Mullen, V.P. of Business Development, InfluxData
• Dipti Borkar, V.P. of Product Marketing, Kinetica
• Crystal Valentine, V.P. of Technology Strategy, MapR
• Jesse Robbins, CEO, Orion Labs
• Lars Knoll, CTO, Qt
• Olivier Pauzet, V.P. and General Manager IoT Solutions, Sierra Wireless
• Jens-Ole Graulund, CTO, Spiio
• Monte Zweben, CEO, Splice Machine
• Shawn Reynolds, CMO, Telit
• Yu Xu, CEO, TigerGraph
• Ray Wu, Founder and CEO, Wynd
• Alex Kubicek, CEO, Understory
• Jeff Finn, CEO, zvelo