Accessibility : Real Time Surveillance & Alerting for Handicapped Parking Spaces enabled with IoT and Deep Learning
Parking space abuse takes place when a person who does not have a disability parks in a handicap space or when placards are loaned out to those that are not disabled. Unfortunately, tickets or any repercussions for parking space abuse is rarely levied and therefore it continues to happen. In a recent May 2018 study handicap accessible parking abuse was witnessed by 74 percent of the participants in the survey.
While overall building accessibility has improved (inside the building) in recent years, if handicapped parking outside the building is misused or abused, that building remains inaccessible.
This accessibility solution is designed to provide real time automation, surveillance, monitoring, and alerting for building security and law enforcement in order to lessen parking space abuse and ensure that buildings are accessible both inside and outside.
Using a combination of commodity hardware devices (Raspberry Pi) to capture and process images of handicapped parking spaces and image classification using Deep Learning models in TensorFlow, parking space abuse can be detected, notifications/alerts sent, and appropriate action taken to ensure that designed parking spaces remain fully accessible and used as they were intended.
Key features of this accessibility solution are as follows:
- Feature 1
- Feature 2
- Feature 3
- Feature 4
- Software or Stack Requirement 1
- Software or Stack Requirement 2
- Software or Stack Requirement 3
- Software or Stack Requirement 4
Clone the Slashmap GitHub repository
git clone (insert URL)
MIT License
Copyright (c) [2018] [Hashmap, Inc.]
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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