AI mapping platform feeds smart city applications
Nexar’s network of “eyes on the road”, edge AI and change detection capabilities aims to tell vehicles what’s coming their way, enabling them to react.
Artificial intelligence (AI) computer vision company Nexar is releasing a real-time mapping (RTM) platform to help cities create mobility applications and services.
CityStream Live is an AI-curated road data feed that can be used by connected vehicles, maps, mobility services, digital twins and smart city applications, to access a continuous stream of fresh, crowdsourced road data.
Edge artificial intelligence
Nexar’s network of “eyes on the road”, edge AI and change detection capabilities aims to tell vehicles what’s coming their way, enabling them to react to varying speed limits, avoid work zones and find parking.
CityStream Live offers users and developers a live data feed to increase situational awareness, enhance driving capabilities, increase safety, add comfort and help solve everyday mobility challenges.
With more than 700,000 vehicles in Nexar’s network of cameras capturing 94 per cent of US roads each month, Nexar reports it collects three billion miles of road vision data per year to support a wide range of urban and highway use cases.
“It allows partners and customers the real-time mapping APIs and tools they need in a technology-agnostic way, independent of the camera or base map used”
Nexar claims that traditional mapping methods like standard- and high-definition don’t provide accurate, up-to-date, and cost-effective solutions. By introducing new and disruptive RTM technologies at the edge of the network, Nexar’s CityStream Live aims to change how road information is captured and delivered to the mobility ecosystem.
“CityStream Live uses the same principles as Google PageRank did back in the ’90s, harnessing crowd wisdom to index the web at 40x lower costs,” said Eran Shir, Nexar’s CEO and co-founder. “This allows partners and customers the real-time mapping APIs and tools they need in a technology-agnostic way, independent of the camera or base map used.”
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Source: Smart Cities World