Active Engineering Food & Agriculture

Smart Synchronised Sensors for Remote Condition Monitoring of Vibratory Systems

In plain English

AI plain-English summary

Sensoteq’s wireless sensors synchronise themselves to monitor large vibrating machinery, such as industrial pumps or turbines, without needing batteries replaced or cables run to each unit. This matters because critical machines—from factory assembly lines to power plant generators—vibrate in complex patterns as they run. If one sensor drifts out of sync with the others, the system cannot build an accurate picture of the machine’s motion. That blind spot means early signs of wear, imbalance, or impending failure go unnoticed until the machine breaks down, forcing costly unplanned shutdowns. The sensors use ultra-low-power electronics and cloud-based artificial intelligence to learn each machine’s normal behaviour. When vibrations deviate from that learned pattern, the system alerts operators before a fault becomes catastrophic. If this technology succeeds, it could transform condition monitoring across heavy industry, energy generation, and manufacturing. Plants would run more efficiently, maintenance could be scheduled rather than reactive, and downtime—which costs industrial sectors millions per day—would drop sharply. The system is fully Internet-connected, so a single operator could monitor equipment scattered across continents from a single dashboard.

View original technical description
Sensoteq has developed a unique Ultra Low Power Technology providing remote continuous measurement in a variety of industrial applications where the environment can be extremely harsh and is constantly changing. In a world of interconnectivity our sensor systems are fully Internet connected offering the ability to monitor and gather data from systems positioned all over the world. By providing secure ways to remotely monitor all type of machines health, we can ensure that end users are alerted to faults ahead of time and can carry out maintenance without having to suffer downtime. Connected to the Cloud, the system uses breakthrough technology to monitor and learn Machine Behaviour through Artificial Intelligence, preventing Machine failure, and running plants more efficiently. For large vibrating machinery, synchronisation of all the wireless sensors monitoring the equipment is key to fully characterise the asset motion, comparing it to expected simulated behaviour and predict early life failure avoiding downtime.

View the original record at the funder ↗

Related Research

Grants with similar aims, by meaning.

Network of Accelerometers for Remote Monitoring
USES of novel Ultrasonic and Seismic Embedded Sensors for the non-destructive evaluation and structural health monitoring of critical infrastructure and human-built objects
Energy Saving Remote Monitoring Solutions
USES of novel Ultrasonic and Seismic Embedded Sensors for the non-destructive evaluation and structural health monitoring of critical infrastructure
Machine Learning for condition monitoring of production equipment

Original classification

Collaborative R&D

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.