access icon free Smart parking sensors, technologies and applications for open parking lots: a review

© The Institution of Engineering and Technology
Received 13/12/2017, Accepted 17/04/2018, Revised 12/03/2018, Published 26/04/2018

Parking a vehicle in traffic dense environments often leads to excess time of driving in search for free space which leads to congestions and environmental pollution. Lack of guidance information to vacant parking spaces is one reason for inefficient parking behaviour. Smart parking sensors and technologies facilitate guidance of drivers to free parking spaces thereby improving parking efficiency. Currently, no such sensors or technologies is in use for open parking lot. This study reviews the literature on the usage of smart parking sensors, technologies, applications and evaluates their applicability to open parking lots. Magnetometers, ultrasonic sensors and machine vision were few of the widely used sensors and technologies on closed parking lots. However, this study suggests a combination of machine vision, convolutional neural network or multi-agent systems suitable for open parking lots due to less expenditure and resistance to varied environmental conditions. Few smart parking applications show drivers the location of common open parking lots. No application provided real-time parking occupancy information, which is a necessity to guide them along the shortest route to free space. To develop smart parking applications for open parking lots, further research is needed in the fields of deep learning and multi-agent systems.

Inspec keywords: intelligent transportation systems; intelligent sensors; multi-agent systems; feedforward neural nets; magnetometers; ultrasonic devices; learning (artificial intelligence); traffic information systems; computer vision

Other keywords: ultrasonic sensors; magnetometers; smart parking applications; multiagent systems; guidance information; deep learning; congestions; smart parking sensors; environmental conditions; environmental pollution; real-time parking occupancy information; parking efficiency; traffic dense environments; convolutional neural network; machine vision; open parking lot

Subjects: Neural computing techniques; Optical, image and video signal processing; Computer vision and image processing techniques; Traffic engineering computing; Knowledge engineering techniques

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