KNL Networks, FLICQ partner to digitize maritime sector with ML-enabled edge sensors

Under the partnership, the maritime sector can monitor vessel machinery in real-time and use predictive analytics by magnetically embedding a FLICQ SmartEdge sensor to the machinery. The sensor collects data and uses AI algorithms to analyze it and send insights to KNL’s Collect device. The information is passed over to the crew and fleet owners through the pole-to-pole network.

“Our collaboration with FLICQ brings to the market a turn-key solution that can transform fleet operations. By combining our solutions, we are able to provide real-time visibility into the health of our customers’ assets and, ultimately, of their operations. By alerting them early of any developing problems we can ensure greater efficiency and effectiveness to save them time and money,” said Toni Lindén, CEO of KNL Networks, in a prepared statement.

FLICQ’s puts algorithms on the chip 

FLICQ’s founders took their experience designing chips for companies like Nortel, Micron, Amazon, and Apple and focused on creating a design that packaged predictive analytics, pattern recognition, or machine learning algorithms onto a battery-operated sensor that can run for up to two years on its own. The self-calibrating chips are used for sensing vibrations and have applications on pumps, motors, and pipes in maritime environments.

There is a wide array of companies providing sensors, but most are designed to simply send data back to an edge gateway or central cloud for analysis. Performing data analysis on the chip enables the sensor to cut down on network traffic, which is where much of the power consumption occurs.

The other aspect of the design is the ease of installation. Customers only need to push a button, attach the sensor magnetically, and wait for it to calibrate.

“It’s like a FitBit for machines,” said Karthik Rau, CEO of FLICQ in a phone conversation with Edge IR. “We usually just ship sensors to customers,” he noted.

Pathways for further growth

The deal with KNL is just one of several that the small company has managed to secure, and Rau feels there is plenty more room for growth without securing a large round of outside funding.

“If you think of assets in the field, only 10% are connected. Companies have to spend a lot of money wiring up and powering up [sensors]. Some equipment has OEM sensors built-in where critical systems are connected, but the vast majority are too old and too remote to be connected in a meaningful way,” said Rau.

“Companies don’t know what assets in the field are doing. Once they have visibility, there’s a lot to do with the data. There’s an opportunity for us to add to an analytics portfolio and to provide insights with practically no latency,” he suggested.

Analysis

FLICQ’s current business model is interesting because it is essentially about selling the algorithms running on the sensors for a monthly fee instead of selling the hardware. Companies are interested in OpEx models, which makes it easier for them to experiment with using technology from a small vendor.

That being said, KNL is probably but the first of several examples of larger network services companies acting as channel partners for FLICQ. Telcos are a natural channel partner-they can bundle in wireless services with the devices and offer value-added data and analytics services to industrial and enterprise customers.

Jim Davis, Principal Analyst, Edge Research Group

Article Topics

FLICQ  |  IIoT  |  KNL Networks  |  machine learning  |  sensors  |  telco  |  wireless