Bernt A. Bremdal

Increasing fall risk awareness using wearables

Each year about a third of elderly aged 65 or older experience a fall. Many of these falls may have been avoided if fall risk assessment and prevention tools where available in a daily living situation. We identify what kind of information is relevant for doing fall risk assessment and prevention using wearable sensors in a daily living environment by investigating current research, distinguishing between prospective and context-aware fall risk assessment and prevention. Based on our findings, we propose a fall risk awareness protocol as a fall prevention tool integrating both wearables and ambient sensing technology into a single platform.

Methodological ReviewIncreasing fall risk awareness using wearables: A fall risk awareness protocol

Each year about a third of elderly aged 65 or older experience a fall. Many of these falls may have been avoided if fall risk assessment and prevention tools where available in a daily living situation. We identify what kind of information is relevant for doing fall risk assessment and prevention using wearable sensors in a daily living environment by investigating current research, distinguishing between prospective and context-aware fall risk assessment and prevention. Based on our findings, we propose a fall risk awareness protocol as a fall prevention tool integrating both wearables and ambient sensing technology into a single platform.

EMPOWER: A network market approach for local energy trade

This paper describes the local market for trade in energy, flexibility and energy related services developed in the ongoing H2020 project, EMPOWER. It is based on a network market approach. The establishment of a local community of prosumers and consumers, inspired by Internet communities, energy cooperatives and online shopping clubs, is central to the idea. At the heart of the community the Smart Energy Service Provider (SESP) can be found. The principal entities and operations associated with the local market concept developed are explained. Some early field results described.

Using Ant Colony Optimization to determine influx of EVs and Charging Station capacities

This paper presents a novel method for determining plug-in Elecric Vehicle (EV) traffic and associated recharging needs based on an ACO (Ant Colony Optimization) method. The method is used to analyze traffic patterns and to determine their impact on the local grid and the design of charging stations. The research reported here also supports the design of a portfolio of Charging Stations (CSs) across a limited geographical area and use this to determine the required capacities of each station. An empirical basis for the research presented has been gathered from Norway where the number of EVs are growing fast and where use of EVs for different purposes, including long-range driving, are becoming very pronounced. The research presented also shows how demand for charging at different times can be determined. This lays the foundation for estimating peak loads in the local grid due to EV charging. For the individual driver the system presented can be used to find preferred routing under different circumstances such as traffic congestion.

Seasonal impacts of EV charging on rural grids

Rural grids might be subjected to seasonal impacts from plug-in electric vehicles (PEV) that need to recharge batteries after medium-distance or long-distance travelling. A case-study from Hvaler, Norway is presented where this phenomenon has been analyzed. New patterns of use and a rapid growth of PEV sales in Norway may represent a future challenge. Traffic waves build up before weekends and bank holidays during spring and summer on roads leading to recreational areas. If the percentage number of PEVs in this traffic increases a concurrent demand for passive battery recharging may occur. It can be shown that this is likely to cause an aggregated load in the rural grid that must be taken seriously. Critical or close to critical situations might occur before special events early in the year, on Fridays during early summer and around Easter. Each of these situations require customized countermeasures.

Fall Risk Assessment and Prevention Using Wearables

Each year about 1/3 of elderly aged 65 or older experience a fall. Many of these falls may have been avoided if fall risk assessment and prevention tools where available in a daily living situation. We identify what kind of information is relevant to do fall risk assessment using wearable sensors in a daily living environment by investigating current research. Based on our findings we propose a fall risk awareness protocol as a fall prevention tool.