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Passive Infrared Sensors (PIR) are inexpensive devices widely used as motion detectors. Standard sensor provides just trigger signal on movement detection. This paper aims to extend standard usage of the sensor from motion detection to motion recognition and activity classification. In applications where motion detection based on video surveillance is not possible due regulations or high costs smart PIR sensor could be the only solution. This publication starts the topic of PIR based motion classification with analyses of hardware requirements and hardware selection for the smart sensor.

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The synchronization of time between devices is one of the more important and challenging problems in wireless networks. We discuss the problem of maximization of the probability of receiving a message from a device using a limited listening time window to minimize energy utilization. We propose a solution to two important problems in wireless networks of battery-powered devices: a method of establishing a connection with a device that has been disconnected from the system for a long time and developed unknown skew and also two approaches to follow-up clock synchronization using the confidence interval method. We start with the analysis of measurements of clock skew. The algorithms are evaluated using extensive simulations and we discuss the selection of parameters balancing between minimizing the energy utilization and maximizing the probability of reception of the message. We show that the selection of a time window of growing size requires less energy to receive a packet than using the same size of time window repeated multiple times. The shifting of reception windows can further decrease the energy cost if lower packet reception probability is acceptable. We also propose and evaluate an algorithm scaling the reception window size to the interval between the packet transmission.

The Ultra-wideband location technology provides high accuracy of indoor positioning. However there is still little work on the accuracy of this solution, especially when monitoring moving objects. The paper shows the results of the measurement of the UWB indoor positioning system accuracy in stationary conditions and shows how the accuracy changes when the monitored object is on the move. It is also measured how the orientation of the antenna influences the accuracy. We show, that while the UWB provides very small error in the stationary scenario (within few centimeters), the accuracy significantly decreases when the device is moving and the average error grows to up to 20 cm. The experimental probability distribution function for different measurement scenarios is presented, showing how the location estimation variates in time and how this is correlated with the actual position of the device.