Manchester-based Autonomous Vehicle software company Wejo Group has announced it’s developing a Neural Edge platform that will enable intelligent handling of data from vehicles at scale, while providing insights that protect privacy and empower automotive innovation.
It says with so much rich data coming from vehicles today, latency and data storage costs are potential obstacles in harnessing and scaling the power of real-time vehicle communications – both with other vehicles and the infrastructure that is set to power Smart Cities. So it’s working with Microsoft Azure to create Wejo Neural EdgeTM, optimising how this data is managed within the vehicle, further processing it at the Edge and ultimately communicating to the cloud.
Wejo believes this process will not only reduce data overload and maximise data insights but will reduce costs for automotive manufacturers and improve manufacturing of the vehicle to provide a better driving experience – supporting safer vehicles, enabling further advancements in EV and autonomous mobility, and reducing congestion and emissions.
“When I started Wejo in 2014, I knew that the proliferation of new mobility technology would drive data to a tipping point. And we are at that point today,” said Richard Barlow, Founder and CEO, Wejo. “With today’s vehicles producing approximately 25 gigabytes of data per hour, and as vehicle technology advances adding more sensors, data filtering and neural edge processing technology is essential to reduce this overload and drive the industry forward. Partnering with Microsoft and Palantir has positioned us to address this problem today, and to look ahead at the benefits of Wejo Neural EdgeTM as a driver in the growth of autonomous mobility. “
In a statement Wejo says Wejo Neural EdgeTM will filter and analyse vast amounts of AV, EV and CV data before transmitting only the essential information to the cloud. This is made possible by utilising in-car edge processing that Wejo is developing to filter only useful and valuable CVD before it is transmitted to the cloud. The embedded software technology in combination with Microsoft Azure cloud computing platform will enable Wejo Neural EdgeTM to power automotive innovation by:
- Reducing network and storage costs for the auto manufacturers by optimising the data coming from the vehicle. Leveraging embedded software within the vehicle chipset, Wejo Neural EdgeTM is designed to intelligently choose and prioritize the data to be sent from the vehicle to the cloud.
- Utilising machine learning algorithms to reconstruct vehicle journey and event data, Wejo Neural EdgeTM can take 20% of the data from autonomous, electric, and other connected vehicles and reconstruct it to represent 100% of the data, without any loss in data fidelity or integrity. The positive environmental impact is significant, as less data requires less storage which in turn reduces power consumption.
- Enabling Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2X) communications. Wejo Neural EdgeTM enables the standardisation and centralisation of the data that comes from autonomous, electric and connected vehicles. Not only does this provide a key building block for communication in near real time, but it also supports communication with infrastructure services such as road signs, traffic lights and parking lots, so vehicles can easily anticipate the road ahead and optimise mobility experiences.
- Delivering a digital twin of the vehicle and cities to reshape how we view the entire product and service ecosystem related to mobility. In a simulation environment, a digital twin of the US can be constructed to simulate how vehicles in different cities need to respond and navigate without having to outlay massive infrastructure costs of physical hardware or vehicles to be able to relearn how a vehicle should behave as an AV or EV, in the Smart City, etc.
“At Wejo, we believe that digital twins will reshape everything from road safety, to insurance, advertising, after-sales and more,” said David Burns, Chief Technology Officer, Wejo. “With Wejo Neural Edge we can look at what a CV is doing a kilometre away, and then alter and change the driver experience of an AV based on the information that is coming from down the road.”