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Bachy Soletanche

Iknaia worked with Bachy Soletanche and artificial intelligence (AI) company AITIS to develop an AI-enabled solution that detects construction site health and safety breaches. The pilot technology was deployed across two of Bachy Soletanche’s major projects.

Iknaia installed a completely standalone communications network and video equipment to capture data to enable AITIS to create AI video analysis. The solution can alert management teams to site health and safety violations in real-time, such as lack of proper safety equipment, employees entering restricted zones and plant/people interface breaches.

The AI identification system means that project managers can be notified of risks before they escalate into real incidents, thus, enabling contractors like Bachy Soletanche to take a more proactive approach to on-site health and safety. Any reported breaches are displayed on an online interactive dashboard, where managers can access evidence of the identified case. If necessary, management can then decide to tailor safety training and procedures accordingly.

Magic Mushroom Company

The Magical Mushroom Company® (MMC) grows mycelium-based packaging as a practical and viable alternative to polluting polymers. MMC had undertaken some work to try to establish the reasons for certain growing behaviours in its trays of mycelium. After a successful KTN Challenge win, the Iknaia team worked with MMC to provide a monitoring solution that included air quality, temperature and colour sensing. We created battery-powered devices and placed these onto the growth trays to monitor the complete growth cycle of the mycelium packaging. A LoRaWAN network was installed so all of the devices could send data to the AWS cloud-hosted servers in real time.

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Clean & Track

Clean and Track was born out of the need to provide data on cleaning events during COVID-19. Clean and Track is a digital real-time recording of cleaning routines undertaken within an outlet. Iknaia, worked with the Clean and Track team to develop the end-to-end solution. We created a bespoke RFID reader that incorporated a cleaning bottle, the reader installed at the base of the bottle was capable of reading RFID tags attached to restaurant tables. The data was sent via Bluetooth to a local detector unit which then sent the data to the cloud for reporting purposes.


Iknaia worked with the Airscan team to create a low-cost environmental monitoring solution. The solution was created using Raspberry Pi technology with integrated air quality sensors.    A 4G router was incorporated into the system to send the data back to AWS cloud-hosted servers.

This end-to-end solution monitors air quality, traffic congestion and acoustic sound, all in one box. The team designed and developed the bespoke branded enclosure, the PCBs, embedded software and the customer-facing dashboard.


Supported by the European Regional Development Fund (ERDF) and led by Rothamsted Research in partnership with the University of Hertfordshire (UH). Iknaia worked with UH to create a remote monitoring water quality solution in fishing lakes. Oxygen levels are critical to the quality and wellbeing of fish stock and when oxygen is below 40% action is required. The team identified and tested several Dissolved Oxygen sensors that could be installed at a lake for a considerable length of time. Embedded software was written to operate the IOT node and backhauled the encrypted data over the Things network.  They identified the processor board, the power board/battery and  created a bespoke enclosure for this successful project. Real-time data was sent to Iknaia’s AWS servers and viewed on an online dashboard.

Smart Bouy Project

Iknaia collaborated with University of Hertfordshire (UH) and Havant based company OSIL on an Innovate UK funded project to create a real-time data buoy to monitor sewage spills in Chichester Harbour.

The team created a bespoke buoy enclosure capable of withstanding the harsh British coastline. Real-time data was sent via the 4G data network up to Iknaia’s AWS servers and a front end dashboard was created to view the data in real-time. Weekly lab test samples were also taken to compare data from the sensors deployed on the buoy. Iknaia worked with UH to create AI Models that were trained using data from the sensors and the lab.  

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