Bluetooth Low Energy (BLE) is currently the dom- inating wireless network solution for eHealth and sports. Howev- er, most BLE sensors require dedicated applications with limited development capabilities. This paper presents a method for rapid development of applications in distributed BLE IoT systems for eHealth and sports. The method is implemented as a JavaScript web framework based on HTML5 canvas, WebSocket and Web Bluetooth APIs. This paper demonstrates how the framework can be applied to develop an application for monitoring physical activity and heart rate. The framework enables software and service operators to iteratively create, tune and deploy filter algorithms in distributed BLE IoT systems, without rebooting nodes or restarting programs using dynamic software updating.

PerfMon is a prototype implementation of a realtime performance management method for sensor data communication in assisted living applications. It is implemented in accordance with the specification for GATT services in Bluetooth low energy (BLE). PerfMon provides a tool for real-time performance monitoring and control for caregivers and service providers. Test results from monitoring and control of packet loss ratio related to alarm thresholds are presented. PerfMon is adapted to cloud-based web services using RESTful APIs and established object models. Performance management is a necessary component in an overall management system of IoT devices for healthcare and assisted living applications.

This paper evaluates a use-case for smartphone-centric Wi-Fi device-to-device sensor communication that enables user mobility in ambient assisted living (AAL) services. A real-time performance measurement method has been developed and implemented to evaluate the smartphone’s ability to act as a hub and gateway for Wi-Fi connected sensor nodes. The results show that Wi-Fi Direct and Wi-Fi Hotspot are feasible solutions for smartphone-centric device-to-device communication that enables user mobility. In addition, a cloud-based web application for monitoring and displaying sensor data has been implemented.

Ambient Assisted Living applications often need to integrate data from multiple sensors, to provide consistent information on the observed phenomena. Data fusion based on samples from several sensors requires accurate time synchronization with sufficient resolution, depending on the sensor sampling frequency. This work presents a technical platform for the efficient and accurate synchronization of the data captured from RGB-Depth cameras and wearable inertial sensors, that can be integrated in AAL solutions. A case study of sensor data fusion for Timed Up and Go test is also presented and discussed.

This paper presents a new algorithm for application layer synchronisation of data from multiple sensors arriving to a mobile phone's Bluetooth interface. A system that provides feedback signals to an athlete is one example where it is crucial to synchronise data from several wireless sensors. This paper also discusses synchronisation problems caused by unpredictable Bluetooth transmission performance. 

Efficient algorithms for time synchronization, including compensation for clock drift, are essential in order to obtain reliable fusion of data samples from multiple wireless sensor nodes. This paper evaluates the performance of algorithms based on three different approaches; one that synchronizes the local clocks on the sensor nodes, and a second that uses a single clock on the receiving node (e.g. a mobile phone), and a third that uses broadcast messages. The performances of the synchronization algorithms are evaluated in wireless personal area networks, especially Bluetooth piconets and ZigBee/IEEE 802.15.4 networks. A new approach for compensation of clock drift and a realtime implementation of single node synchronization from the mobile phone are presented and tested. Finally, applications of data fusion and time synchronization are shown in two different use cases; a kayaking sports case, and monitoring of heart and respiration of prematurely born infants. 

This paper presents a method to synchronize the clocks in a Bluetooth piconet from the application layer in a mobile phone. It adapts algorithms for time synchronization of distributed systems and the Internet to Bluetooth networks. The performance issues that cause problems for data synchronization between master and slaves in Bluetooth are highlighted. The tests show that the synchronization error is limited to one sampling time.