9 automotive startups using machine learning and deep learning

Spark – Optimizing Electric Vehicle Performance


British startup Spark develops software based on machine learning. Their app analyzes the distance an electric vehicle can travel on a full charge – an estimate based on a variety of parameters like terrain and performance on recent trips. It is worth noting that behavioral assessments are made for both unmanned electric vehicles and man-driven vehicles.

iGloble – Machine Learning for Quality Control


Indian startup iGloble’s product is called calHled Connected Design, and it uses machine learning and AI. calHled Connected Design refines the design of automotive parts used in the manufacturing process. It also optimizes production runs and reduces downtime by predicting equipment failures using real-time 3D simulations.

SONICLUE – Preventive maintenance on sound analysis


Israeli company SONICLUE creates a product that uses machine learning and signal processing technologies. This product allows engineers and auto mechanics to troubleshoot vehicle problems through sound vibrations. Defects and malfunctions of all components cause certain fluctuations, and SONICLUE software detects them, so that the mechanic can deal with the specific faulty component.

SO NAH – Smart Parking


German startup SO NAH develops a platform based on machine learning – this platform is based on smart sensors, and with their help, provides information on the availability of free parking spaces. These sensors can be installed in any infrastructure and can also be integrated with any technology – for example, with existing video surveillance systems.

Autonomous Fusion – Machine Learning for Self-Driving Vehicles


American company Autonomous Fusion, formerly known as Wheego Technologies, is working on a deep learning solution. The company’s products are intended to improve the performance of ADAS systems and improve the reliability of self-driving cars. Autonomous Fusion products predict the nature of the events a vehicle is facing and, through a combination of proprietary and open machine learning technologies, enable the vehicle to respond in a fraction of the time.

Deep learning

Hazen.ai – Intelligent Traffic Management System


Hazen.ai Is a Saudi Arabian startup that develops smart traffic cameras. These cameras analyze the video stream and use deep learning techniques to detect dangerous driving. The analysis is carried out in real time, so that the actions of drivers are recognized, and warnings and fines are automatically sent to violators.

RoadE – Vehicle Status Tracking


Indian startup RoadE develops predictive maintenance systems for vehicles. RoadE’s video processing utility is based on deep learning and video stream analysis, while the Auto Smart platform uses a combination of machine and deep learning for 24/7 vehicle health monitoring. Thus, the company can predict the need for maintenance, so that the car will not be idle for unnecessary time in the service center.

Univrses – Unmanned vehicles


Swedish startup Unvrses develops computer vision solutions for the urban environment. The 3DAI City platform is based on their proprietary 3DAI engine and uses video cameras installed in public transport. As vehicles move along the route, the platform collects various data, which is later used to improve object recognition systems in unmanned vehicles.

MDGo – Customer Data Management


Israeli startup MDGo uses deep learning and a suite of sensors in its solution that collects data about vehicles during an accident. MDGo’s software analyzes collisions in real time and sends data to hospitals and emergency responders. This product allows you to optimize the work of doctors and provide effective treatment for victims, reducing the risk of chronic damage. In addition, this solution allows you to smoothly settle insurance issues.

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