Systematic design of an embedded neural system for automated visual consumption acquisition

Automated consumption meter readout is a subject of commercial interest, because a vast number of installed mechanical meters have to be read manually today. Visual readout by attachment of an embedded system comprising dedicated image sensor, processor, and transmission system as an add-on to existing installed meters is an interesting alternative to the expensive replacement by electronic meters with remote readout. With regard to the underlying large number of potential installation sites, this problem is also an instance of an application where a dedicated implementation can compete with general purpose hardware concerning size and costs. In our approach, we focuses on the compact, cheap, and energy conserving implementation of a neural embedded system for this application. This work also serves as a research vehicle for the long term objective of developing a methodology for systematic and optimized integrated cognitive system design