Bluetooth Low Energy (BLE) is currently the dominating wireless network solution for eHealth and sports. However, 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.

Bluetooth Low Energy (BLE) is a wireless communication technology for Internet of Things (IoT) applications. Although recent versions of BLE embrace the 6LoWPAN standard for IPv6 low-power device communication, this is often not the best choice for constrained-node networks due to downsides such as increased memory and computation overhead, heavier network stack, increased power consumption, backward incompatibility, etc. A crucial requirement for successful IoT solutions is an efficient strategy for monitoring and control of highly distributed sensor nodes. In this paper, we propose a dynamic and lightweight model for management of distributed constrained BLE nodes based on OMA Lightweight M2M (LWM2M) protocol. To this end, we have designed a new intermediate component, a BLE-LWM2M gateway (GW), which has dual roles: a BLE master that monitors and controls the BLE devices, and a LWM2M client that acts on behalf of an operator's LWM2M management server. The BLE-LWM2M GW has interfaces to dynamically manage connected BLE devices as LWM2M objects, called ObjectTwins, in runtime without a need for user configuration. All services that BLE devices provide are mapped to the ObjectTwins in the gateway, which are exposed to the LWM2M server. Hence, this model enables a LWM2M server to manage distributed BLE devices by interacting with the BLE-LWM2M GW using the LWM2M standard methods, and the constrained devices can still use a native Bluetooth communication protocol. To verify its feasibility, a prototype of a mobile healthcare system has been implemented in a testbed.

Bluetooth Low Energy (BLE) is a wireless communication technology for Internet of Things (IoT) applications. Although recent versions of BLE embrace the 6LoWPAN standard for IPv6 low-power device communication, this is often not the best choice for constrained-node networks due to downsides such as increased memory and computation overhead, heavier network stack, increased power consumption, backward incompatibility, etc. A crucial requirement for successful IoT solutions is an efficient strategy for monitoring and control of highly distributed sensor nodes. In this paper, we propose a dynamic and lightweight model for management of distributed constrained BLE nodes based on OMA Lightweight M2M (LWM2M) protocol. To this end, we have designed a new intermediate component, a BLELWM2M gateway (GW), which has dual roles: a BLE master that monitors and controls the BLE devices, and a LWM2M client that acts on behalf of an operator's LWM2M management server. The BLE-LWM2M GW has interfaces to dynamically manage connected BLE devices as LWM2M objects, called ObjectTwins, in runtime without a need for user configuration. All services that BLE devices provide are mapped to the ObjectTwins in the gateway, which are exposed to the LWM2M server. Hence, this model enables a LWM2M server to manage distributed BLE devices by interacting with the BLE-LWM2M GW using the LWM2M standard methods, and the constrained devices can still use a native Bluetooth communication protocol. To verify its feasibility, a prototype of a mobile healthcare system has been implemented in a testbed.

This paper presents a multi-layer distributed performance management model for Internet of Things (IoT) as a service for caregivers. Performance monitoring and control of IoT devices and services are vital functions for e-health systems. Cloud-based IoT systems with centralized data centers further underline the need for distributed management. The main contribution of this paper is a model and prototype implementation that combines low-complexity policy-based and conventional network management with cloud computing paradigm, lightweight IoT protocols, and their data models. A case study on monitoring of heart activity demonstrates interworking between OMA Lightweight M2M protocol, Bluetooth low energy GATT services, and Azure IoT hub cloud platform to enable distributed policy-based performance management.

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.

Fall injury issues represent a serious problem for elderly in our society. These people want to live in their home as long as possible and technology can improve their security and independence. In this work we study the joint use of a camera based system and wearable devices, in the so called data fusion approach, to design a fall detection solution. The synchronization issues between the heterogeneous data provided by the devices are properly treated, and three different fall detection algorithms are implemented. Experimental results are also provided, to compare the proposed solutions.

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.