Archive 27/02/2024.

Improving Actuarial Models with Sensorless Remote Monitoring Networks

john.grant

How the insurance industry will develop remote monitoring networks to offer personalised insurance

Remote monitoring can involve collecting behavioural data using telematics apps on smartphones or wearables. Sensorless, or non-invasive sensing without sensors, is an emerging field in remote condition monitoring. Radio-frequency devices built from commodity equipment, such as Wi-Fi, are being used to remotely monitor machinery by analysing how mechanical components modulate the surrounding radio-frequency spectrum. Machine learning is used to detect subtle changes in the motional signature which opens the way for a new branch of predictive maintenance.

As sensorless technology evolves, commodity remote monitoring programmable devices will be used to monitor home appliances such as washing machines, dishwashers and refrigerators. These may be distributed by insurance companies to offer personalised insurance or service plans. Consumers may be incentivised to install monitoring devices and sell their telemetry data via smart home hubs to independent remote monitoring networks.

The logistic efficiency of delivery robots and drones will significantly decrease shipping costs. Conversely, Jevons paradox means the transport of physical goods will increase. However, an increasing proportion of those goods will be shared through short term rentals. This will lead to the emergence of new rental markets and the sharing economy. Sharing more goods will reduce the aggregate demand of those goods. Remote monitoring will be useful here to monitor the health and usage patterns of equipment.

Mining telemetry data networks will help designers build better and more energy efficient products. Predictive maintenance will help to minimise failures and improve safety. Increasing the lifespan of equipment will maximise the use of materials, reduce energy consumption and waste, helping to contribute towards climate change mitigation.

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