ID: MRFR/ICT/1318-HCR | November 2022 | Region: Global | 110 pages
Impact of COVID-19 on the Crowd Analytics Market
The outbreak of COVID-19 has crippled the global economy. Enterprises from several industry verticals have incurred heavy financial losses due to the lockdowns enforced by governments across the globe to prevent further spread of the infection. Retail outlets, supermarkets, malls, offices & workplaces, transport systems including airplanes, rail, and road, hospitality, hotels & restaurants, bars & clubs, schools, colleges, and universities have been affected severely. Similarly, manufacturing has been restricted to permitted limits. However, the lockdowns are now being lifted gradually to help the sectors recover and stimulate the global economy.
Crowd analytics technology has helped healthcare and other institutions during the current crisis. With the integration of artificial intelligence, big data, and analytics tools, crowd analytics solutions are helping institutions to comply with C-19 regulations by enabling them to monitor the live occupancy of areas, detect human body temperatures in crowds, detect face masks, recognize faces, and analyze audiences in realtime. According to the WHO statistics, globally, around 646,000 people die from fatal falls each year. Also, according to the National Council on Aging, an elderly falls prey to accidents every 11 seconds, and one senior citizen loses their life from falling incidents every 19 minutes. While industry verticals are re-opening slowly, crowd analytics solutions are assisting the security and governing agencies in analyzing and managing situations beforehand by detecting abnormal human behavior, predicting uncertain situations, detecting anomalous body temperatures, and so on. Thus, helping prevent the spread of COVID-19 without hampering day-to-day operations. Furthermore, thermal detection systems detect and reveal the distribution of temperatures in each area through the use of IR and thermal cameras, detecting potentially sick or infectious individuals in a crowd. These data sets generated are used in different ways helping authorities trace, track, predict, and contain the spread of the disease.