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This project is funded as a CASE studentship through the Integrated Electronics Manufacturing Research Centre, UK (IEMRC) and NP Aerospace Ltd, Coventry.
Team: John Kemp, Dr Elena Gaura, Dr James Brusey.
The monitoring of hazardous environments, along with the people working within them, is an area which lends itself to applications of wireless and body sensor networks. The field is rich with potential applications in detecting hazards, providing feedback to observers and other critical tasks that can increase the safety and overall working conditions of people operating in these environments.
Bomb disposal suits contain a large amount of padding and armour to protect the wearer's vital organs in the case of explosion. The combination of the heavy (roughly 40kg) suit, physical exertion, and the environment in which these suits are worn can cause the wearer's temperature to rise to uncomfortable and potentially dangerous levels during missions. Current cooling systems used in the suits in question are provided with manual control but this may be distracting to operate; additionally, battery life is limited and, if cooling is left on, the batteries will be exhausted well before the end of a normal mission.
To address the above problems, this project aims to design, implement, and embed into the suit a body sensor and actuation network that will:
A secondary goal of this project is to aid the suit manufacturer in better understanding how the suit material and design choices are affecting the wearer's thermal comfort during use.
A prototype system has been developed which both satisfies the need for remote monitoring and allows for future integration of a cooling automation component to ensure effective, need-based cooling. The need for detailed measurement of skin temperature, the applicability of body sensor network technology to this application domain, and the suitability of modelling thermal sensation based on skin temperature have all been positively assessed and experimental validation has taken place. A modelling engine (based on a Bayesian Network) is being developed, which will allow the assessment of thermal comfort in real-time using gathered sensor data. Posture will feature as a factor in the predictive component of the modelling engine in order to allow the effects of changing airflow to be accounted for. The thermal comfort model will be used to control the actuation of cooling. Work is on-going towards real-time posture determination based on integrated accelerometers, and the development of the multi-modal modelling engine.
For details of ongoing work go to John's PhD project page.