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Environmentally-powered wireless sensors use ambient energy from their environment to support their own energy needs. As such, they must operate without significant maintenance or user supervision. Due to the stochastic availability of ambient energy, its harvesting, storage and consumption must be managed by an efficient and robust controller that maintains data collection and transmission rates at desired levels, while maximizing the useful operational time of the system. To accomplish this task, the control system must observe the state of charge of an internal energy storage device, and consider the amount of energy available for harvest in the future. At the same time, the complexity of the controller must be limited so that it can be implemented on the simple embedded system of the sensor hardware. This paper presents a comprehensive synthesis of desired behavior of such controllers, and describes procedures for their design and optimization through an evolutionary fuzzy approach. The main contribution is the formalization of design objectives and development of the fitness function that drives the optimization process. Additional contributions include a comprehensive evaluation of several soft computing optimization approaches, thorough analysis of the optimized controller, its comparison to baseline control strategies, and validation of its operation with real energy availability forecasts. [ABSTRACT FROM AUTHOR]

In this paper we propose the WNMCL algorithm that allows iteratively locate unknown wireless nodes. The algorithm requires only one mobile node, which collects RSS signal from other nodes with unknown position and approximates their distance by path-loss model. These data are used for the probability occurrence correction of the nodes in the space modelled by Monte Carlo. The WNMCL algorithm was validated using simulations and the results are presented in this paper. [ABSTRACT FROM AUTHOR]

People suffering from diabetes mellitus are dependent on exact blood glucose concentration information. This information is vital for their successful treatment and protection against life threatening extremely low or high blood sugar levels. Solution described in this paper integrates blood glucose evaluation and treatment recommendation, where all the information like body sensitivity to insulin and carbohydrate to insulin ratio is used to calculate recommended amount of next insulin dosage or food. This solution also supports strip with damaged insertion signal line. Device prototype had been developed and successfully tested on three subjects with diabetes I and two with diabetes II. [ABSTRACT FROM AUTHOR]

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