Agriculture
June 4, 2024
Epicollect5
Read SolutionImplemented by
Imperial College London
Updated on June 28, 2024
·Created on October 21, 2020
Derq is an AI based application for road safety prediction and traffic analysis.
Derq is an AI-based application using cameras and sensors to predict cars and pedestrian behaviour on the road. It also provides alerts to connected cars and road owners in case of danger on the road. This application aims to increase road safety.
Target SDGs
SDG 9: Industry, Innovation and Infrastructure
Target Users (Target Impact Group)
Household, Community
Distributors / Implementing Organizations
MOU with Government of Dubai
Manufacturing/Building Method
This product is currently in the prototyping phase and not yet manufactured at scale.
Intellectural Property Type
Copyright
User Provision Model
Road owners or electric car manufacturers can reach out to Derq for installation and deployment of the application
Distributions to Date Status
None
Expected lifespan (years)
N/A
Maximum span (m)
N/A
Maxiumum load (kg)
N/A
Design Specifications
Derq is a system relying on Artificial Intelligence and V2X (Vehicle to Everything) to increase road safety. The system relies on the network of roadside cameras to predict pedestrian and car behaviour. The cameras equipped with sensors would be placed at roadsides and at busy junctions. They could then scan for poor driving and high speed. The system would collect all these data. Derq’s patented technology uses the data to send an early-warning or alert message about the danger from other vehicles to drivers of cars in the network, such as sensing when a driver at an intersection would run a red light. The system would then alert other drivers in a 2 s time lapse.
Technical Support
Unknown
Replacement Components
N/A
Lifecycle
N/A
Manufacturer Specified Performance Parameters
Safer, smarter roads using AI
Vetted Performance Status
Tests have been running in Dubai, no results are available
Safety
Unknown
Complementary Technical Systems
None
Academic Research and References
Halim, Z., Kalsoom, R., Bashir, S., and Abbas, G., 2016, Artificial intelligence techniques for driving safety and vehicle crash prediction. Artificial Intelligence Review, Springer Netherlands.
Compliance with regulations
Unknown
Evaluation methods
Testing on roads equipped with cameras
Other Information
More information about the product is contained in this article; Can smart sensor systems anticipate and avoid danger?
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