Periodic Reporting for period 1 - EoT (Eyes of Things)
Okres sprawozdawczy: 2015-01-01 do 2016-06-30
In this context, the challenge that motivates this proposal can be summarized as follows:
• Future embedded systems will have more intelligence and cognitive functionality. Vision is paramount to such intelligent capacity.
• Despite advances in connectivity, cloud processing of these images captured ‘in the edge’ is not sustainable. The sheer amount of visual data generated cannot be transferred to the cloud. Bandwidth is not sufficient and cloud servers cannot cope with it. This means that processing has to be brought to the edge (i.e. to the device itself). Additionally, for the embedded device, it is not efficient to transmit images themselves. It has been shown that, compared to local computation, transmitting data out of the device (for off-line processing) is several orders of magnitude more expensive in terms of energy consumption
• Unlike other sensors, vision presents enormous challenges that have not yet been tackled such as the ratio of power consumption vs processing power, size and cost. This is currently an inhibitor of further research and innovation.
Our aim in project “Eyes of Things” is to develop an an optimized open vision platform that can work independently and also embedded into all types of artefacts. The platform is optimized to maximize inferred information per milliwatt and adapt the quality of inferred results to each particular application. This will not only mean more hours of continuous operation, it will allow to create novel applications and services that go beyond what current vision systems can do, which are either personal/mobile or “always-on” but not both at the same time. The EoT platform targets OEMs and the estimated unit cost of $15 makes it suitable for mass consumer products. The design and development will be followed by the use of the platform in 4 demonstrators spanning surveillance, wearable and embedded configurations.