Iris Automation gets funding for plan to bring AI to commercial drones

Iris Automation gets funding for plan to bring AI to commercial drones

Collision avoidance provider Iris Automation has received $ 8 million funding to bring its AI technology to autonomous drones and other flying vehicles.

In October 2015, Iris Automation’s founders put fingers to keys and wrote the company’s first lines of code. Two months later, they had a prototype for a system that aims to tackle the three big challenges facing the industrial drone industry: reliability, safety and autonomy. Their collision avoidance system for commercial drones promises to unlock the potential of beyond line-of-sight use cases.

After humble beginnings, the San Francisco-based company was accepted into the Y-Combinator start-up accelerator program in 2016 and, just yesterday, announced $ 8 million of Series A funding, led by Bessemer Ventures, to bring their AI-powered technology to life.

“Iris’ exceptional team has unlocked a $ 100 billion global industry by ensuring aviation safety in a world serviced by drones. No other technology comes close to their system in providing situational awareness in a feasible package for the flying robotics industry,” said David Cowan, the partner at Bessemer who led rounds in aerospace innovators like Skybox, Rocket Lab and Spire Global.

The operation of UAVs beyond line-of-sight without suitable sense and avoid systems is largely forbidden by regulatory bodies. That’s why, if drones are to become more widely useful, autonomous tools for industry, they need intelligent situational awareness technology.

Read more: Can drones and commercial aircraft safely share airspace?

The case for autonomous drones

Regardless of how skilled a drone pilot may be, it can be difficult to see hazards, due to the reliance of onboard cameras at longer ranges. Collisions can have expensive, or even tragic, consequences. When a company can’t demonstrate adequate mitigation of operational risk, regulators must limit drone applications.

Iris’s solution combines computer vision and deep learning algorithms to allow the drone to see the world much like a human pilot does – identifying potential hazards and intuiting speed and distance. The plug-and-play system interweaves basic deterministic algorithms with more advanced, non­deterministic algorithms and neural networks, which allow the system to be fault tolerant.

Harnessing this technology, the platform can detect distant objects, identify it (as a light aircraft, for example) and estimate its distance. A sophisticated logic core then autonomously manoeuvres the drone (or other flying robot) out of a collision trajectory.

Read more: Drones offer a new perspective on British Columbia wildfires

Rising above the competition

“Iris Automation’s approach to sensing is unlike anything ever attempted in the autonomous vehicle space,” said Alexander Harmsen, CEO at Iris Automation. “Our team of experts in computer vision, machine learning, and traditional aviation have built a product that will provide the level of safety necessary for pushing the boundaries of what is possible with drones, at a size factor and price point unheard of in the world of aviation.”

For all the artificial intelligence and machine learning power behind of its software, it’s somewhat surprising to learn that the hardware employs smartphone camera technology – but given the economies of scale of such devices, the cost, weight and power-intensiveness of radar, and the low resolution, unproven potential of LiDAR, it’s a shrewd choice.

“With a range of over 1,500ft, our system is 50x more powerful than the ‘bumper solutions’ that some current drone companies are using today with a mere 30ft detection range. Furthermore, the product is a standalone unit, agnostic to all platforms and can be integrated into any commercial drone in the world,” revealed Alejandro Galindo, Head of R&D.

Iris Automation
The Iris Automation team in its early days, working out of a basement (Credit: Iris Automation)

Read more: Parrot revamps consumer drones for commercial market

Autonomous drones: the business applications

Industrial drone operations using pilots would not be economically viable for many companies. The more cost-effective ability to fly autonomously and Beyond­Visual­Line­of­Sight (BVLOS) would pave the way for new methods of pipeline inspection, package delivery, large agribusiness, mining exploration, and much more besides.

Currently in open beta, Iris Automation is looking for partners in the UAV and drone space for its Early Adopter Program. Regulatory exceptions for BVLOS flights in the US Federal Aviation Administration’s (FAA) UAV rules (referred to as Part 107) allow drone companies to trial new technologies. There’s an opportunity to apply for BVLOS operations through the waiver process by using the Iris System before it is commercially available.

With its latest funding, Iris Automation is looking to expand its team (which already boasts expertise from the likes of NASA and Boeing) and scale its technology to participate in the upcoming White House UAS Integration Pilot Projects. Given, their product, talent and increasing financial backing, we could soon see myriad Iris-equipped autonomous drones rising out of Silicon Valley.

Read more: DJI launches FlightHub for drone fleet management

The post Iris Automation gets funding for plan to bring AI to commercial drones appeared first on Internet of Business.

Internet of Business

FieldIn AgTech startup grabs $4M in new funding

Fieldin, an end-to-end pest management software using sensors to automatically record field data to make any tractor smart raised $ 4M in new funding. The round was co-lead by Gal Ventures and Germin8 Ventures.

Record and organize notes automatically on a native mobile app synced to the cloud.

Fieldin operates in the AgPest (Agricultural Pesticide) market and monitors pesticide and sprays used by professional specialty crop farmers. Designed essentially for perennial crops and primarily aimed towards for orchard, grove and vineyard growers.

The startup uses its sensor-based device appended to tractors to provide real-time speed, location, coverage and efficiency logs. It then uses the data to recommend spray methods and routine helping to correct spraying mistakes. The cloud-based software of Fieldin can be used to gain a situational view of pest levels, spray history and hotspots.

Performance reports summarizing activity trends and patterns

One of the key factors that are helping Fieldin gain a leg up over its competitors is the number of ‘sprayed acres’ it has monitored over the past two years (which according to the startup’s own estimate equals 1 million). This has helped the startup create a vast ‘AgPest Dataset’.

“Our AgPest dataset has reached a critical-mass coverage that enables us to provide unique insights on crops, chemicals, and geographies. We started our initial activities in Israel and expect to cover over 40 percent of the citrus and vine markets in 2018. Fieldin is rapidly expanding to the US, Europe and Africa, and has landed major contracts with some of the biggest names in the industry.”
Boaz Bachar, Founder and CEO of FieldIn.

There’s been an uptick in the number of AgTech startups using a combination of hardware and software to provide farm data. Farmobile that raised a $ 18.1M Series B in Nov last year also uses a small device called PUC that installs on farm machinery. It then collects data wirelessly and relays to its cloud platform where it uses analytics to help farmers take corrective actions.

Similarly, the Australian startup The Yield raised $ 6.5M Series A funding in April last year where by the startup provides on-farm sensors and hardware with an advanced data analytics platform for farmers to improve crop yield and reduce weather-related uncertainty.


Postscapes: Tracking the Internet of Things

Akita raises $700,000 crowd-based funding on Kickstarter

Akita, an IoT device watchdog station raised approximately $ 700,000 crowdfunding on Kickstarter. With 7000 plus backers, the startup promises to provide instant privacy for connected products.

Instant Privacy for Smart Homes

The device performs three core activities i.e. scans connected gadgets/devices, blocks compromised devices and notifies the users of known issues. Akita comes with full support and help desk monitoring powered by Axius.

This device connects to a LAN port on users’ home router (not inline). The startup describes the device working as follows:

“Akita uses a custom form of WiFi sniffing to detect questionable packets and send them to our servers to be analyzed (this is why the hardware can run on low memory/CPU, because it’s mainly a cloud-based system). Once the packets are determined to be malicious, a command is sent from our servers back to the Akita device; this includes custom protocol commands to disconnect the device from the network router.“

Akita’s Kickstarter received significant backing (both in terms o the number of backers and funds raised from the campaign), though, it only aimed to raise $ 30,000 initially.

The rise in popularity of privacy and network security devices is understandable. A home network, with several connected devices, need robust protections. That’s where other startups like Dojo and F-Secure also promise to secure network traffic and identify rouge devices.

Readers might visit the Postscapes Connected Device Security guide to understand how other devices in the same niche work and how Akita stacks up against its competitors.


Postscapes: Tracking the Internet of Things

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The Next Web

How to accurately value your startup for your next funding round


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This story continues at The Next Web
The Next Web