Localization of missing entities using parked cars

Verago, Rudi; Naoum-Sawaya, Joe; Griggs, Wynita M.; Shorten, Robert

doi:10.1109/iccve.2015.8

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…With expanding on-board sensor complements, computing, and communication abilities, parked cars no longer need to be idle, to be of no service to us during the extended periods when they are not being driven. Recently [6,17,18], the use of networks of parked vehicles in dense urban areas has been suggested for the detection and localisation of moving, missing entities using RFID technology.…”

Section: Introductionmentioning

confidence: 99%

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Predictability and Fairness in Social Sensing

Ghosh,

Marecek,

Griggs

et al. 2020

Preprint

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In many applications, one may benefit from the collaborative collection of data for sensing a physical phenomenon, which is known as social sensing. We show how to make social sensing (1) predictable, in the sense of guaranteeing that the number of queries per participant will be independent of the initial state, in expectation, even when the population of participants varies over time, and (2) fair, in the sense of guaranteeing that the number of queries per participant will be equalised among the participants, in expectation, even when the population of participants varies over time.In a use case, we consider a large, high-density network of participating parked vehicles. When awoken by an administrative centre, this network proceeds to search for moving, missing entities of interest using RFID-based techniques. We regulate what vehicles are actively searching for the moving entity of interest at any point in time. In doing so, we seek to equalise vehicular energy consumption across the network. This is illustrated with simulations of the search for a missing Alzheimer's patient in Melbourne, Australia.

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Section: Introductionmentioning

confidence: 99%

“…For example, police are able to go to the location at which the entity was detected in order to refine the localisation and determine whether the entity needs assistance, and if required, aid the entity on its way home. See [6,17,18] for further details. The work presented in [18] was simulation-based.…”

Section: Introductionmentioning

confidence: 99%