8 Hot IoT Startups to Watch in 2017

Which up-and-coming IoT companies will make the biggest splash next year?

When people ask, “What is the Internet of Things?” we usually think of consumer devices like wearables or gadgets for smart homes.

But behind the scenes in the enterprise world—manufacturing, construction, logistics, retail, transport, power production and distribution—a revolution is happening. Internet of Things (IoT) technology and applications are bringing intelligence and insight to previously unconnected devices like lighting and heating systems, vehicles and even farmland.

“Behind the scenes in the enterprise world, an IoT revolution is happening.”

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The IoT secret for businesses is not just collecting the data but turning it into effective insights that improve how work is done. That means bringing information from all of your enterprise’s disparate systems into one place to create true insight and understanding into how your business works.

So what’s in store for IoT in 2017? Who will power this technology revolution? Let’s explore eight great, young companies who look set to make a big impact in the IoT evolution in the next 12 months—and beyond.

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Foghorn

IoT is creating a different model of computing. Instead of using a central data center sucking in data from a distributed network, this new architecture of IoT is pushing intelligence to the edge of systems.

Imagine a huge network of devices and sensors collecting data. Bringing that huge mass of raw information to the center is expensive, wasteful and difficult. Instead, it’s better to push the information out to the edge, which reduces bandwidth and latency and accelerates decision-making.

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Californian startup Foghorn creates a stack of specialized software to allow this to happen. Its software ingests locally created sensor data and processes it to create useful insights.

It can then communicate via the cloud to centralized management systems that use machine learning and advanced analytics to improve operational intelligence, create schedules for predictive maintenance and optimize use of assets. Foghorn and its model is likely to be crucial to the success or failure of intelligent IoT projects.

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Sparkcognition

SparkCognition is another company using AI to help businesses deal with the massive data load created by IoT networks. It uses artificial intelligence, or cognitive infrastructure, to make sense of the exponential growth in data. SparkCognition has created three key IoT applications: SparkSecure (to secure systems), SparkPredict (to predict maintenance) and DeepArmor (a beta project to protect networks from malware attacks).

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SparkCognition CEO Amir Husain’s biggest priority for 2017? “Scaling flawlessly.” The company has experienced great success in all three core verticals of energy/manufacturing, finance and government. Husain added, “We are now working feverishly to scale the business development and business delivery teams to fulfill demand.”

According to Husain, IT leaders will be focused on two key things for IoT in 2017: “ensuring security and gaining usable, meaningful insight from the data that IoT systems are gathering already.”

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3

Crowdoptic

San Francisco-based CrowdOptic brings together three of the hottest areas of emerging technology: wearables, augmented reality and IoT.

CrowdOptic describes itself as creating “Middleware for Wearables.” It uses patented technology to triangulate the position of objects, which smartphones or other devices are filming. This has been used by special forces to improve target acquisition and to live-stream video back to command headquarters. By triangulating data from several devices, CrowdOptic gives commanders a three-dimensional view of the battlefield.

It is beginning to be used by fire services and other first responders to improve decision-making by giving commanders a far clearer view of how incidents are evolving.

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Surgeons are also using the technology to live-stream operations. Students, or overseeing surgeons, can see exactly what is happening and provide real-time feedback.

By 2017 you might see maintenance companies using the devices to live-stream exactly what engineers are seeing in the field and request assistance from experts back in the office.

The company has just launched its own device, CrowdOptic Eye, to send high quality, encrypted video and audio over Wi-Fi, Ethernet or LTE networks.

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CrowdOptic describes itself as creating “Middleware for Wearables.” It uses patented technology to triangulate the position of objects, which smartphones or other devices are filming.

4

Evrything

London-based Evrything is a visionary of IoT evolution. It takes IoT beyond specific devices and sensors. Instead, its ambition is to give a digital address to literally everything—all the physical objects in a supply chain or every product or piece of packaging a company makes.

It has built a cloud-based smart platform to collect data from all these separately identified objects. As more and more products get “smart,” the platform will allow real-time inventory and logistics tracking. But it also creates a new communication channel between companies and consumers. Diageo in Brazil sold whisky bottles with QR codes, which allowed people to record personal video messages linked to bottles given away as gifts.

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The platform uses open standards to feed information into other enterprise applications like CRM or marketing systems. It promises to provide semantic meaning and business logic to live IoT data.

The company is very much at the cutting edge, but we might start seeing wider use of smart packaging in the next few years.

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London-based Evrything is a visionary of IoT evolution. It takes IoT beyond specific devices and sensors, instead its ambition is to give a digital address to literally everything—all the physical objects in a supply chain or every product or piece of packaging a company makes.

5

Enevo

Finnish startup Enevo has more down-to-earth ambitions: to make rubbish collection smarter, cheaper and better.

It uses simple wireless sensors to tell when a bin is full and even predict when it will be full. Data is transferred via 2G and 3G networks free of charge—Enevo has agreements with all the major carriers. The device is ruggedized, waterproof and the battery should last for 10 years.

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Combined with intelligent mapping technology, this allows collection trucks to be sent on the quickest, greenest route to empty those bins. Empty bins don’t have to be checked and a simple tablet application tells truck crews where to go. The company claims savings of up to 40 percent are possible as well as reducing noise and pollution from trucks driving to empty bins.

Enevo software can create a 30 day route plan and sends individual routes to the relevant tablet every day.

The sensor can also create alerts for unexpectedly full bins and bins that have been moved or tipped over.

Customers are limited right now but you might see an Enevo sensor in a bin near you soon.

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Senseye

Many IoT platforms are aimed at large enterprises, which can afford serious investments in data analysis and networks or already have big IT departments.

But Southampton-based university spin-off Senseye has created a web-based system to provide the same functions for small firms with less to invest. (The name comes from “sensei,” the Japanese word for teacher or master.)

Senseye provides manufacturing companies with predictive analysis built on machine learning. This can provide predictive failure and maintenance warnings to tell you when machines, or even parts of machines, are likely to fail or require repair or replacement.

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Senseye’s latest project aims to bring IoT to agriculture. It is deploying sensors on organic farms around the southeast of England to monitor soil moisture, humidity and even some air particles. 

This is combined with open source data like weather forecasts and historic performance to create a picture of current, and likely future, state of crop health and performance for farmers planning for harvest or irrigation.

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7

Dat-uh

Canadian-based Dat-uh has built a cloud-based platform that can collect data from a wide range of IoT devices,sensors and other systems.

It then contextualises the data—searching for patterns and hidden correlations using machine learning to constantly improve its understanding of the data collected. Finally, the system changes this historic understanding into useful predictions to prevent failures and downtime, optimize use of resources and predict future energy use.

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The early stage startup is focused on renewable energy, manufacturing, agriculture and battery capacity predictions for electric vehicle. In 2016, Dat-uh’s founder and CEO Humera Malik received the Connected World’s M2M Women of the Year Award, which recognizes her contributions for fostering the growth of technology in the IoT/machine-to-machine space.

 

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Canadian-based Dat-uh has built a cloud-based platform that can collect data from a wide range of IoT devices, sensors and other systems.

8

Drayson Technologies

In a gold rush, the people selling shovels make most of the money. Similarly, when it comes to emerging technologies, the companies that build the platforms capture the lion’s share of the market.

Drayson Technologies—who’s tagline is “Making the IoT easy”—is one such platform contender. The London-based company has made it its mission to reduce the “ballooning energy consumption of IoT networks” and has devised two technologies to solve this problem.

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Sensyne is a machine learning software platform for building complete end-to-end IoT solutions. It is intended to be the “brain” of sensor networks.

Freevolt enables a continuous power supply to very low energy IoT devices. This greatly extends the lifespan of sensor batteries, and could potentially eliminate the need to charge via a cable. This is done through RF energy harvesting, drawing on sources such as microwave, cellular, Wi-Fi and digital TV when sufficient RF density is available, or through inductive power transfer using a dedicated transmitter.

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Drayson Technologies has made it its mission to reduce the “ballooning energy consumption of IoT networks” and has devised two technologies to solve this problem.

 

 
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