Motion control in environmental biorheology using inductance signal processing
Autor: | John Ronczka |
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Rok vydání: | 2016 |
Předmět: |
Engineering
Signal processing Focus (computing) Active perception business.industry Context (language use) Control engineering Motion control Motion (physics) Variety (cybernetics) Visualization 03 medical and health sciences 0302 clinical medicine Human–computer interaction 030212 general & internal medicine business 030217 neurology & neurosurgery |
Zdroj: | AMC |
DOI: | 10.1109/amc.2016.7496320 |
Popis: | This paper utilizes a road network robotic system called a ‘Traffic Control Signal’ (TCS). The TCS uses a variety of active sensing (‘active perception of motion’ (APMs)) but the focus will only be on pavement bicycle inductance loops. This leads to an entanglement of functionality of signal processing for motion control of Humans-to-robotic to power recharging, and enhance communications for people with vision and hearing impairments for wayfinding. Inductance loop development is likely to be driven by increasing community expectations for inclusive sustainable technologies with low whole of life costs. Secondly, to improve communications between Human-to- machines-to-entities to achieve an inclusive ‘Internet of Things’ (IOT) ecosystem. In this paper, the focus is on existing technologies (‘off-the-self’ [OTS]) that may be re-engineered and then re-purposed. The context relates to in-pavement loops as an enabler to the development of Bio-communications between machines-to-entities for ‘Internet of Things’ (IOT) motion control. Existing technologies may be able to be re-purposed and reused as ‘off-the-self’ (OTS) technologies to achieve future needs (must have) and wants (like to have) of Human-to-robot interaction. The outcome desired is a visualisation method to map the surface pattering of the unique active sensing (‘active perception of motion’ (APMs)) and then mitigate any constraints that limit an inclusive ‘Internet of Things’ (IOT) ecosystem. |
Databáze: | OpenAIRE |
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