Development of PAN (personal area network) for Mobile Robot Using Bluetooth Transceiver

In recent years, wireless applications using radio frequency (RF) have been rapidly evolving in personal computing and communications devices. Bluetooth technology was created to replace the cables used on mobile devices. Bluetooth is an open specification and encompasses a simple low-cost, low power solution for integration into devices. This research work aim was to provide a PAN (personal area network) for computer based mobile robot that supports real-time control of four mobile robots from a host mobile robot. With ad hoc topology, mobile robots may request and establish a connection when it is within the range or terminated the connection when it leaves the area. A system that contains both hardware and software is designed to enable the robots to participate in multi-agent robotics system (MARS). Computer based mobile robot provide operating system that enabled development of wireless connection via IP address

Safe and Secure Wireless Power Transfer Networks: Challenges and Opportunities in RF-Based Systems

RF-based wireless power transfer networks (WPTNs) are deployed to transfer power to embedded devices over the air via RF waves. Up until now, a considerable amount of effort has been devoted by researchers to design WPTNs that maximize several objectives such as harvested power, energy outage and charging delay. However, inherent security and safety issues are generally overlooked and these need to be solved if WPTNs are to be become widespread. This article focuses on safety and security problems related WPTNs and highlight their cruciality in terms of efficient and dependable operation of RF-based WPTNs. We provide a overview of new research opportunities in this emerging domain.Comment: Removed some references, added new references, corrected typos, revised some sections (mostly I-B and III-C

Energy managed reporting for wireless sensor networks

In this paper, we propose a technique to extend the network lifetime of a wireless sensor network, whereby each sensor node decides its individual network involvement based on its own energy resources and the information contained in each packet. The information content is ascertained through a system of rules describing prospective events in the sensed environment, and how important such events are. While the packets deemed most important are propagated by all sensor nodes, low importance packets are handled by only the nodes with high energy reserves. Results obtained from simulations depicting a wireless sensor network used to monitor pump temperature in an industrial environment have shown that a considerable increase in the network lifetime and network connectivity can be obtained. The results also show that when coupled with a form of energy harvesting, our technique can enable perpetual network operatio

Low-Power Synchronization for Multi-IMU WSNs

Wireless time synchronization is one of the most important services in a Wireless Sensor Network (WSN). Inertial Measurement Units (IMUs) are often used in these WSNs in healthcare-related treatments. We present a low-power, wirelessly synchronized multi-IMU platform. The proposed approach synchronously captures packets from different IMUs and transmits the data over Bluetooth Low Energy (BLE) to a central Data Capturing Unit (DCU). The contribution of this work is, rather than focussing on the highest possible accuracy, to provide a low-power accurate enough solution for use in a multi-IMU WSN. We examine key factors affecting synchronization accuracy and elaborate on the implementation challenges. An accuracy of sub 1 us can be achieved with the approach using 74.8 J/h of energy, while a power-optimized implementation is presented with an accuracy of 200 us and an energy consumption of only 198 mJ/h. This approach suits the required accuracy and low-power requirements for a multi-IMU system

Energy and Accuracy Trade-Offs in Accelerometry-Based Activity Recognition

Driven by real-world applications such as fitness, wellbeing and healthcare, accelerometry-based activity recognition has been widely studied to provide context-awareness to future pervasive technologies. Accurate recognition and energy efficiency are key issues in enabling long-term and unobtrusive monitoring. While the majority of accelerometry-based activity recognition systems stream data to a central point for processing, some solutions process data locally on the sensor node to save energy. In this paper, we investigate the trade-offs between classification accuracy and energy efficiency by comparing on- and off-node schemes. An empirical energy model is presented and used to evaluate the energy efficiency of both systems, and a practical case study (monitoring the physical activities of office workers) is developed to evaluate the effect on classification accuracy. The results show a 40% energy saving can be obtained with a 13% reduction in classification accuracy, but this performance depends heavily on the wearer’s activity