How can we use sensors to map the streets to check which street
has parking?
How can we use sensors to map the streets to check which street
has parking?
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Now, we will try to learn About how we can use sensors to map
the streets to check which street has parking.
As the number of vehicles continues to grow, parking spaces are
at a premium in city streets.
Additionally, due to the lack of knowledge about street parking
spaces, heuristic circling the blocks not only costs drivers' time
and fuel, but also increases city congestion.
In the wake of recent trend to build convenient, green and
energy-efficient smart cities, we rethink common techniques adopted
by high-profile smart parking systems, and present a user-engaged
(crowdsourcing) and sonar-based prototype to identify urban
on-street parking spaces. The prototype includes an ultrasonic
sensor, a GPS receiver and associated Arduino
micro-controllers.
It is mounted on the passenger side of a car to measure the
distance from the vehicle to the nearest roadside obstacle.
Multiple road tests are conducted around Wheatley, Oxford to
gather results and emulate the crowdsourcing approach.
By extracting parked vehicles' features from the collected
trace, a supervised learning algorithm is developed to estimate
roadside parking occupancy and spot illegal parking vehicles.
A quantity estimation model is derived to calculate the
required number of sensing units to cover urban streets.
The estimation is quantitatively compared to a fixed sensing
solution.
The results show that the crowdsourcing way would need
substantially fewer sensors compared to the fixed sensing
system.
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