An embedded wireless system for estimating the exposition risk in first emergency management

Abstract In this paper we propose the design of a wearable embedded system1 for wirelessly delimiting an hazardous area during emergency, alerting the rescue operators when entering in it and measuring the consequent exposition time. (The dangerous area is previously identified, e.g., through suitable instrumentation). The suggested approach, which is identically effective in indoor and outdoor environments, significantly extends existing solutions by not requiring any absolute position information for delimiting the hazardous area or fixed infrastructure as requested instead by GPS and UWB solutions. The proposed low-power system can be easily retrieved after use and ready to be deployed in a new environment.</jats:p

An Adaptive Sampling Algorithm for Effective Energy Management in Wireless Sensor Networks with Energy-hungry Sensors

Energy conservation techniques for wireless sensor networks generally assume that data acquisition and processing have energy consumption that is significantly lower than that of communication. Unfortunately, this assumption does not hold in a number of practical applications, where sensors may consume even more energy than the radio. In this context, effective energy management should include policies for an efficient utilization of the sensors, which become one of the main components that affect the network lifetime. In this paper, we propose an adaptive sampling algorithm that estimates online the optimal sampling frequencies for sensors. This approach, which requires the design of adaptive measurement systems, minimizes the energy consump- tion of the sensors and, incidentally, that of the radio while main- taining a very high accuracy of collected data. As a case study, we considered a sensor for snow-monitoring applications. Simulation experiments have shown that the suggested adaptive algorithm can reduce the number of acquired samples up to 79% with respect to a traditional fixed-rate approach. We have also found that it can perform similar to a fixed-rate scheme where the sampling frequency is known in advance