Camera networks are typically used for large-scale high value security applications such as person tracking in airports or amusement parks. However, current cameras are expensive and have only very limited mobility, acting as a barrier to their wider adoption. However, body worn cameras are able to overcome this problem and are widely worn by personnel of various industries. This is evidenced by the rapid growth of leading Body Worn Camera (BWC) company Edesix Ltd, whose VideoBadge technology is being adopted by security and police forces worldwide. In addition they make a valuable extension to static camera networks in crowded areas and public events. Nevertheless, these cameras are usually not networked and are stored and purely used as evidence.
Here, we look into introducing networking capabilities into these mobile cameras and interweave them with existing security infrastructure. Introducing the capability to process the captured imagery online ensures video data is not necessarily leaving the individual BWC system and only aggregated data is communicated within the network. Smart mobile camera networks are a challenging and ideal domain to push beyond the state-of-the-art in algorithms for adaptation and self-organisation. Through the use of these new techniques, the individual mobile cameras are able to provide their users with valuable feedback about the current network-wide situations and might alert them about events not within their own field of view. Self-organisation will enable rapid system-wide reconfiguration in response to emerging events.
Edesix Ltd supports the SOLOMON project with its state-of-the-art BWCs and will exploit the outcomes of the project to provide on-site operators with tools to make fast and well-informed decisions.
The SOLOMON project is funded by the European Union Horizon 2020 programme under the Marie Sklodovska-Curie scheme. The project is carried out by Aston University, Edesix Ltd, and the University of Birmingham. For more details please contact Dr. Lukas Esterle (email@example.com)
This work was supported by the SOLOMON project (Self-Organisation and Learning Online in Mobile Observation Networks) funded by the European Union H2020 Programme under grant agreement number 705020.