The Bluetooth Low Energy (BLE) MESH network technology gains popularity in low duty IoT systems. Its advantage is a low energy consumption that enables long lifetime of IoT systems. The paper proposes and evaluates new MRT management methods, i.e. exact and heuristic, that improves energy efficiency of BLE MESH network by minimizing the number of active relay nodes. The performed experiments confirm efficiency of the MRT methods resulting in significantly lower energy consumption of BLE MESH network.
In this paper, an autonomous wearable sensor node is developed for long-term continuous healthcare monitoring. This node is used to monitor the body temperature and heart rate of a human through a mobile application. Thus, it includes a temperature sensor, a heart pulse sensor, a low-power microcontroller, and a Bluetooth low energy (BLE) module. The power supply of the node is a lithium-ion rechargeable battery, but this battery has a limited lifetime. Therefore, a photovoltaic (PV) energy harvesting system is proposed to prolong the battery lifetime of the sensor node. The PV energy harvesting system consists of a flexible photovoltaic panel, and a charging controller. This PV energy harvesting system is practically tested outdoor under lighting intensity of 1000 W/m2. Experimentally, the overall power consumption of the node is 4.97 mW and its lifetime about 246 hours in active-sleep mode. Finally, the experimental results demonstrate long-term and sustainable operation for the wearable sensor node.
Localization systems are an important component of Active and Assisted Living (AAL) platforms supporting persons with cognitive impairments. The paper presents a positioning system being a part of the platform developed within the IONIS European project. The system’s main function is providing the platform with data on user mobility and localization, which would be used to analyze his/her behavior and detect dementia wandering symptoms. An additional function of the system is localization of items, which are frequently misplaced by dementia sufferers.
The paper includes a brief description of system’s architecture, design of anchor nodes and tags and exchange of data between devices. both localization algorithms for user and item positioning are also presented. Exemplary results illustrating the system’s capabilities are also included.