{"id":15299,"date":"2021-10-12T00:00:00","date_gmt":"2021-10-11T23:00:00","guid":{"rendered":"https:\/\/members.dataiq.global\/articles\/ai-in-formula-e\/"},"modified":"2021-10-12T00:00:00","modified_gmt":"2021-10-11T23:00:00","slug":"ai-in-formula-e","status":"publish","type":"article","link":"https:\/\/www.dataiq.global\/devstage\/articles\/ai-in-formula-e\/","title":{"rendered":"AI in Formula E: Winning on the racetrack – and against climate change"},"content":{"rendered":"

Formula E is defined by cutting-edge technology and fine margins. All participating vehicles are built on the same chassis and powered by the same battery. Uniformity of hardware means that teams rely on data and insight to gain strategic advantages. \u201cThe cars are essentially computers on wheels, without IT infrastructure they wouldn\u2019t move an inch,\u201d says Filippi. \u201cBecause of this, we have to be the best we can be in terms of analytics and AI.\u201d Genpact\u2019s AI-based technology combines third-party data on weather and track conditions with millions of data points generated by the Envision Virgin Racing vehicles \u2013 including information on alignment, speed, acceleration and battery usage \u2013 to inform strategic decision making at lightning speed.<\/p>\n

Generating insights at pace is particularly important within Formula E. The format differs from most motorsports by holding its practice, qualifying and competitive races on the same day. Envision Virgin Racing has a distinct advantage in this area: a state-of-the-art simulator housed in the team facility at Silverstone. \u201cWe\u2019re often racing on tracks we\u2019ve never been to before – the simulator allows us to correlate augmented data with live data on race day to make necessary changes to the car in a very short space of time,\u201d says Filippi.<\/p>\n

The team has had a further advantage this season thanks to Genpact\u2019s Radio Analytics Engine (RAE), which was unveiled to the sporting world last month<\/a>. RAE uses advanced AI and analytics to process and structure the hours of radio chatter generated by drivers and their teams on race day. Insights that would be impossible to generate by ear are relayed to drivers as structured signals to inform split-second decision making on the track. \u201cRacing is a dynamic sport, nobody can predict how the race is going to pan out and that\u2019s part of the fun,\u201d says Filippi. \u201cThanks to RAE, we\u2019re able to generate structured, real-time insight into what our opponents are doing for the first time – adding a new layer to what we are able to do on the track.\u201d<\/p>\n

Genpact\u2019s chief digital officer Sanjay Srivastava believes that the need to generate insights at pace is true \u201cnot just in motorsport, but across the board.\u201d The company deploys similar cutting-edge AI and analytical technologies in the corporate arena; its insurance claims platform quickly turns vast amounts of information \u2013 including auto accident images, home damage and claims submissions \u2013 into insights to support liability and pay-out decisions. \u201cFrom the racetrack to the boardroom, for insights to be actioned you need to have solid data foundations,\u201d says Srivastava.<\/p>\n

The Envision Virgin Racing team is as dedicated to winning the race against climate change as it is to winning on the track. Envision is a green technology company geared towards helping partner organisations reach net-zero carbon emissions. Together with Virgin Racing it has launched the Race Against Climate Change platform, which aims to accelerate the transition to renewable energy and the proliferation of electronic vehicles. By applying the same Genpact technology used to win on race day, the team has automated the process for monitoring its carbon-footprint. By regularly supplying automated reports to sustainability partner the Carbon Trust, Envision Virgin Racing became the first team in Formula E to earn carbon-neutral accreditation. \u201cWe\u2019re the greenest team on the greenest grid,\u201d says Jennifer Babington, operations director and general counsel and Envision Virgin Racing. \u201cThis is guilt-free, environmentally conscious motorsport and the technologies that we\u2019re establishing on the track will have a direct impact on society as a whole.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

Formula E is defined by cutting-edge technology and fine margins. All participating vehicles are built on the same chassis and powered by the same battery. Uniformity of hardware means that teams rely on data and insight to gain strategic advantages. The Envision Virgin Racing Team has partnered with professional services firm Genpact to maximise its drivers\u2019 chances on the track.<\/p>\n","protected":false},"author":17,"featured_media":15300,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"categories":[129,398],"tags":[217,791,218,793,493,792],"pillar":[],"class_list":["post-15299","article","type-article","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-public","tag-ai","tag-analytics","tag-artificial-intelligence","tag-formula-e","tag-insight","tag-racing"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 01:42:51","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/15299","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/article"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/17"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=15299"}],"version-history":[{"count":0,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/article\/15299\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/15300"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=15299"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=15299"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=15299"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=15299"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}