Analytics Insight explains some reasons for India to lag behind the US and China in the AI race

Being the second most populated country in the world, India is still lagging behind the US and China in the AI race, even in 2021. The US is positioned at the number one in the AI race for a long time while China is motivated to take over the position. These two countries are currently the leaders of Artificial Intelligence with proper infrastructure for R&D. It is a well-known fact that India is a developing country and the US, as well as China, are developed countries in the world. But there are other reasons for India to lag behind these two countries in the AI race. This article explores a few reasons for the readers to have a better understanding.

India is thriving with a domestic market with skilled laborers in 2021. But, there is a lack of reputed technology companies in the market to invest time in R&D for innovating machines and models with cutting-edge technologies. The US and China have Google, Microsoft, Baidu, and Alibaba respectively to create new innovations for the welfare of society. Google, IBM, Microsoft, and many other reputed tech companies have extended their market in India and are recruiting Indian employees for better productivity. But India is lagging behind in the AI race because the country does not have crazy and obsessed entrepreneurs like Elon Musk and Jeff Bezos.

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India is one of the most educated countries in the world, with numerous educational institutions. Gradually the education sector is integrating technical courses and curriculum in Artificial Intelligence, Machine Learning, and Robotics in the form of Mechatronics. Students only know about those five traditional engineering courses but there is a wide array of engineering in these disruptive technological fields. They are slowly taking interest in these fields due to more exposure to globalization and digitization. There are a handful of Ph.D. scholars or engineers who are highly interested to develop new machines with these cutting-edge technologies. Thus, it will take some time for India to educate students and inspire them to be in the field of Artificial Intelligence and innovate new AI models efficiently and effectively.

Another reason for India to lag behind the US and China in the AI race is the lack of publishing research papers. China and the US have each published more than 15,000 AI research papers in recent years. It is observed that the average US research quality is better than in China or the EU. The US is becoming the world leader in designing AI chips for smart systems. India has integrated Artificial Intelligence and machine learning only in the field of computer science.  India is required to boost research tax incentives as well as expand the array of public research institutions to work on AI research papers. This will help in the creation of better efficient machine learning algorithms to take a lead in the AI race.

China has strict control over its population index with specific rules and regulations, for citizens to manage data explosion efficiently. The country receives sufficient and appropriate volumes of real-time data to train Artificial Intelligence models. It has a strategic priority to drive the Chinese tech companies in creating a plethora of potential AI applications with this data. Meanwhile, India does not have control over the population along with undocumented citizens. The rural sector still lacks proper internet connection, leading to a digital divide in the country.  It is more difficult for India to receive appropriate data from both urban and rural sectors.

The Indian government needs to articulate an ambitious mission on Artificial Intelligence for more innovations. The government is required to understand that India needs Artificial Intelligence to drive success and revenue for the nearby future. There are multiple sectors that need AI to boost productivity. There are certain progressive start-ups growing up in the domestic market to help the industries.

But it is better late than never. India should realize the power of useful knowledge from the enormous sets of data available due to digitization. This knowledge will help the country to solve its own problems and achieve five-year plans efficiently and effectively. There should be a key focus on developing advanced and modern data infrastructure to be in the AI race with the US and China.

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Due to the public outcry and tax cuts, companies are going green with AI to prevent irreversible harm to the planet.

We are the first generation to witness the effects of climate change unfold, and the last with the ability to prevent those effects from intensifying and irreversibly harming our planet.

According to the US Environmental Protection Agency, global carbon emissions from fossil fuels rose significantly since 1900. CO2 emissions have increased by about 90% since 1970, with emissions from fossil fuel combustion and industrial processes contributing about 78% of the total greenhouse gas emissions increase from 1970 to 2011.

These insights are not new to operators of industrial plants and factories. China is followed by the US and the EU as the largest emitters of CO2. They collectively account for over 50% of global emissions.

Most industrial facilities are well aware of their carbon footprint. Due to public demand for environmental sustainability and higher taxes on emissions, they have every intention to implement decarbonization measures. For the most part, however, their efforts have fallen short, leaving a gap between their ambitions and the reality of their carbon reduction activities.

According to the Boston Consulting Group, the standard three-step approach to implementing decarbonization measures starts with assessing the carbon footprint and comparing it against the carbon footprint of industry peers, as well as national/international standards. The next step is to develop realistic short- and long-term decarbonization targets based on a thorough cost-benefit analysis. The final step is to define the specific measures that will provide environmental and economic benefits.

Most industrial plants and factories already have the necessary capabilities to go green, both in terms of production and logistics. Depending on the industry, the necessary change may be a switch in energy sources, such as solar and wind in place of coal and fossil fuels. In most cases, however, the change calls for an upgrade in processes and technologies for increased efficiency. Some companies, such as the Israel-based EcoPlant, are working to tackle that challenge before it’s too late.

EcoPlant, which has offices in Israel and the US, developed a SaaS (Software as a Service) solution that connects to air compressors’ controllers and property sensors to monitor and continuously optimize entire systems. Their predictive AI algorithms conduct ongoing energy surveys and dynamically control each compressor and the whole system.

The end result? Significantly reduced energy waste, increased reliability, and optimized maintenance. Such a solution enables continuous savings of hundreds of thousands of dollars annually. EcoPlant’s proprietary algorithms can also be applied in settings such as hospitals and commercial buildings, as well as critical infrastructure equipment, such as pumps and chillers, essentially making it a one-size-fits-all solution.

The harmful effects that stem from energy waste and CO2 emissions undoubtedly trace back to human decisions and errors. Undoing those negative effects, especially in the modern post-pandemic world, requires the collaborative efforts of human intelligence with machine intelligence. Numerous facilities hailing from industries with the largest carbon footprints, such as technology, automotive and process industries, are already getting on board with AI solutions such as EcoPlant, to meet popular and regulatory demands.
According to the Paris Climate Agreement, which is an ambitious global action plan to fight climate change and its negative impact, emissions from production and logistics would need to drop approximately 45% by 2030 to be on a path to meet the 1.5°C target for limiting the global temperature increase. To meet this goal, it is imperative for industrial plants and factories to ramp up their efforts to go green by turning to AI.

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HOHHOT, June 17 (Xinhua) — As a drone buzzed overhead taking aerial photos of the prairies in north China’s Inner Mongolia Autonomous Region, Zhang Wenbiao took soil samples on the ground.

Work in the area has been going on since May. It involves an intensive “physical check” on an 18,333-hectare area of Xilingol Grasslands, one of the four major pastoral regions in Inner Mongolia, before starting a comprehensive grassland restoration program.

The project, the first of its kind to treat grassland degradation in the region, uses a big data platform jointly established by the government of East Ujimqin Banner and M·Grass Ecology, a tech firm in Inner Mongolia, to restore the grassland’s ecosystem.

The samples brought by Zhang and his colleagues to the company’s lab for analysis showed poor soil nutrition.

Based on the data about soil, water and geological conditions obtained from satellite photographs and precision photos taken by drones, the big data platform has selected different grass species adapted to growing on different areas of the prairies from the system’s database containing information of 62,000 varieties of plant germplasm resources.

“Understanding nature’s language is the first step in the restoration process. For us, nature talks in data,” said Chen Yufeng, deputy general manager of the M·Grass grassland restoration project.

Seeding machines have been installed to carry out mass sowing in the grasslands with seeds selected by the company. Chen said that they are using the rainy season from May to July for the planting, which is conducive to the survival of the vegetation.

Wednesday marked the World Day to Combat Desertification and Drought, which is aimed at raising awareness of international efforts to tackle the challenge of desertification.

According to figures from the forestry and grassland administration of Inner Mongolia, by 2019, the average vegetation coverage of Xilingol Grasslands had reached 46.78 percent, an increase of 16 percentage points in 20 years thanks to a comprehensive effort of ecological rehabilitation.

“The ecological restoration concept that we advocate is to understand nature rather than to conquer it,” said Xu Min, chief information officer of the big data subsidiary of M·Grass Ecology.

The company has planned to install a large number of sensors to monitor soil and air conditions on the prairies for timely evaluation of the progress of the grassland restoration program.

“If we continue to feed the ‘brain’ (of the platform) with data, it can help calculate information such as grassland bearing capacity to indicate how many sheep and cows can be raised at the most,” said Chen.

The region has been committed to striking a forage-livestock balance in the pastoral areas by providing subsidies to herdsmen to limit the number of their livestock since 2011 while carrying out programs to protect grassland biodiversity.

Du Senyun, deputy director of the forestry and grassland administration in East Ujimqin Banner, said that larger hay yield of the grassland means bigger size of flocks and more money in herdsmen’s pockets, and a higher vegetation coverage attracts more tourists.

M·Grass Ecology had earlier been involved in programs treating fragile ecology problems such as degraded land, deserted mines, and saline-alkaline land in Xinjiang Uygur Autonomous Region, Tibet Autonomous Region as well as Yunnan and Shaanxi provinces in west China. Enditem

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With glowing blue eyes and trusting feline features, a new robot cat by Chinese startup Elephant Robotics seems happily oblivious to the worries of CEO Joey Song as he shows it off at the company’s lab in Shenzhen.

Elephant Robotics’ main business is the automation of factory assembly lines but revenue has plunged by a third this year due to the coronavirus, leading the company to cut staff by a fifth.

“It’s tough,” said Song. “Before, we had more than 30 people.”

Due to the downturn, the firm is putting more energy into the robot cat project funded on Kickstarter in December. Readying its first large batch of 1,000 cats for sale, it hopes that as more consumers work from home, interest in pet robots will grow.

“If the industrial robots can’t sell right now, we just focus on other robots to lower the risks,” Song said.

Interest in robots has surged worldwide as the pandemic forces hospitals, manufacturing and services companies as well as governments to look afresh and with new urgency at ways to minimise human contact.

But in China, months ahead of many countries in reopening its economy and the world’s biggest market for industrial robots, new business seems largely limited to robots for warehouses and disinfecting. Most clients are now too spooked by the uncertain business climate to invest in expensive factory gear, industry executives say.

“Automation should be a way to fight virus consequences but on the other side if you want to invest, you need to know the market forecasts,” said Vincent Bury, managing director at equipment maker CNIM China. “Nobody has a crystal ball now.”

China’s industrial robot sales tumbled by a fifth in the first quarter from a year earlier, according to Shanghai-based consultancy Stieler Enterprise. It predicts second-quarter sales will likely decline 15%.

While the pain is being felt widely, major players in China such as Switzerland’s ABB, Japan’s Yaskawa Electric Corp and Germany’s Kuka AG are expected to weather the storm.

But for domestic robotic startups that have hitched their prospects to a broad shift within Chinese manufacturing to more automated factory lines, the rest of this year could be make or break. Access to fresh funding is tight as venture capitalists wait to see which firms will survive the immediate downturn.

“We’d love to wait for another one or two months (before investing) to see how they’ve recovered, whether it’s going to get back to normal,” said the vice president of an investment firm with several interests in China’s robotics industry.

He declined to be identified to protect business relationships.

FINGERS CROSSED

For startups that either specialise in or have managed to pivot to cleaning or warehouse-related robots, prospects have become brighter after more than a month of lockdown disrupted China’s supply chains and made fulfilling orders tricky.

“We’re struggling, luckily struggling,” said Lawrence Han, chief technology officer at Triooo, a maker of industrial cleaning robots backed by Taiwan’s Foxconn and based in the high-tech hub of Shenzhen. “I think our product was delayed by almost three months.”

Triooo is working to clear a backlog of orders and hopes to eventually sell in Western markets where its robots, used in places like hospitals and airports, are more cost-effective due to higher labour costs there.

Beijing-based Geek+, a maker of robots that transport and stack goods in warehouses, opened its San Diego office in February just as supply chains in China ground to a halt. After three months of uncertainty, it suddenly saw demand soar as the spread of the virus spurred consumers to shift most of their shopping online, said Mark Messina, chief operating officer of Geek+ Americas.

At Youibot, which specialises in robots for power stations and furnaces, the outbreak prompted the company to develop a robot that can patrol public spaces, scanning body temperatures and emitting a virus-killing ultraviolet light when people are not around.

The Shenzhen-based startup has found buyers in Italy, Singapore and Turkey, while the American Institute of Minimally Invasive Surgery is also trialling a batch.

“This product’s biggest value to us is that it gives us experience deploying robots overseas and provides us with different ways for our business to develop,” said Youibot CEO Cody Zhang.

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Guian New Area, a national-level new urban area in Southwest China’s Guizhou province, plans to build itself into one of the largest big data clusters globally over the next few years as part of its broad push to develop new infrastructure to stoke a fresh growth engine for the region, a local official said.

Chen Yan, a deputy to the 13th National People’s Congress, told China Daily during the ongoing two sessions meeting that the new area plans to “hub 12 mega data centers and 4 million servers with a fixed-asset investment of over 40 billion yuan ($5.6 billion) by 2025”.

“We are scrambling to build the new area into the country’s largest data center that is secure, green and intensive. We also plan to build it into the biggest data cluster nationwide and even worldwide,” said Chen, who is also the mayor of Guiyang and director of the Working Committee of Guian New Area.

“This year, a string of data centers, including that of Apple’s iCloud and tech giant Huawei Technologies’ Co, will be completed in the new area,” he said.

The move is part of Guiyang’s bigger plan to speed up the development of new infrastructure, so as to spur a new wave of growth in the face of the global novel coronavirus outbreak.

“Data centers, as the basic infrastructure of cloud computing, are an indispensable part of the big data industry chain. It is also a new infrastructure that is supported by the country currently,” Chen added.

China has called for accelerated efforts to develop new infrastructure. Differing from traditional infrastructure like railways, highways and airports, the new type of infrastructure projects include infrastructure for digital transformation, intelligent upgrades and innovative development.

To embrace new industrial opportunities, Chen pointed out the area will leverage new infrastructure to promote deeper digital transformation and high-quality economic development.

“A string of new infrastructure projects will speed up construction in Guiyang and the new area and a total of 23 billion yuan of investment on new infrastructure is expected to embark within the year,” Chen added.

“The new area will also accelerate its steps in gathering companies from emerging sectors including cloud computing, big data, the internet of things and artificial intelligence. This will support new consumption formats such as telecommuting, intelligent medical care, online education, and fresh food e-commerce,” he said.

Nestled in a mountainous region, Guiyang and the Guian New Area provide a major engine of growth for the region. It has been transformed in the past few years into an innovation hub as major global companies such as Apple, Huawei and Alibaba Group Holding Ltd flocked to the area.

“Guizhou has already become an important part of the big data industry in China and even the world. The company will strengthen cooperation with Guizhou in a string of areas including cloud computing and digital governance,” Huawei Vice-President Lu Yong said.

Last year, over 100 big data projects valued at a total of 21.6 billion yuan were introduced in Guiyang. The city’s software and information technology revenue exceeded 16 billion yuan, having increased by 14.3 percent year-on-year.

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Chinese biomedical data is mostly stored in centers hosted by foreign countries and therefore could be at risk from hacking, a deputy to the National People’s Congress from Shanghai has warned.

Li Lin, a member of the Chinese Academy of Sciences (CAS) and a researcher at the CAS Center for Excellence in Molecular Cell Science, said that while the US, Europe and Japan have bioinformatics centers with 200PB of data, the BIG Data Center of the Beijing Institute of Genomics of CAS, which is the leader of such centers in China, only has a storage capacity of under 10PB.

The same problem is reflected in the global research on the origin of the molecules of the COVID-19, Li said.

“The genomic data of COVID-19 from China was uploaded to the GISAID (Global Initiative on Sharing Avian Influenza Data) which serves as the source of data for large-scale computing,” he said. “Also, Chinese scientists are dependent on software for gene and protein sequence analysis developed by foreigners.”

This, according to Li, affects the efficiency of data mining and the formation of knowledge for Chinese scientists.

Li advised that the central government embark on the integration of health data kept by research institutes, medical institutions, government agencies and various companies and the establishment of technical standards for such data to push for efficient collection and application of the data while intensifying research infrastructure innovation.

“There are a few health data platforms in China, but there is no unified and authoritative one such as the HealthData.gov of the US and the Data.gov.uk of the UK,” Li said.

He suggested that besides the rooftop national bioinformatics center, the government should establish regional data junctions at the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the Guangdong-Hong Kong-Macau Greater Bay Area.

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The automatic operation and maintenance of optical network is important for ensuring information communication and network operation. The growing variety of services has forced operation and maintenance personnel to face tremendous operational pressure. A recent study has constructed a control architecture called intent defined optical networks (IDON) to cope with the issue.

The research related paper “Intent Defined Optical Network with Artificial Intelligence-based Automated Operation and Maintenance” is recently published in a special focus on artificial intelligence for optical communications in Science China Information Sciences. The paper is lead by Hui Yang as the corresponding author and associate professor of Beijing University of Posts and Telecommunications. Researchers have adopted a self-adapted generation and optimization policy (SAGO) to perform control research on intent defined optical network architectures, revealing two key closed-loop operations, namely closed-loop strategies generation and closed-loop intent guarantee.

Traditionally, the operation and maintenance of optical networks rely on the experience of engineers to configure network parameters, including command line interfaces, middleware scripts, and troubleshooting. With the rapid development of Internet of Things and high bitrate applications beyond 5G and 6G, a large number of applications are presented on the network in the form of intentions, such as the Internet of Vehicles which closely interact with the environment. As an important support of the policy of “network power,” the optical network faces the challenges of accurate match of the intent application and the complex control of highly dynamic applications, resulting in unsatisfactory levels of manual operation and maintenance. In such cases, operators urgently need to consider the upgrade of their optical network architecture to achieve automatic intelligent operation and maintenance.

Research on intent defined optical networks (IDON) introduces an adaptive generation and optimization (SAGO) strategy in a self-optimizing way. The IDON architecture can achieve intent-oriented configuration conversion, realize adaptive generation and optimization strategies, and perform closed-loop intent-guaranteed operations. IDON specifically addresses communication intent and uses natural language processing to construct semantic graphs to understand, interact, and operate the required network configuration. Then, deep reinforcement learning (DRL) is utilized to dynamically integrate fine-grained strategies to find a synthesis strategy which meets the requirements of the intent. Finally, a deep neural evolution network (DNEN) was introduced to respond to failures to achieve intent guarantee at the millisecond level. The researchers have validated feasibility and efficiency on an enhanced SDN test platform.

These results have enriched the research on intelligent operation and automation of optical networks based on artificial intelligence. IDON with SAGO is not only of great significance to the research of operation automation of optical networks, but also has very important scientific significance and reference value for the application of zero-touch operation and artificial intelligence in networks.

“To the best of our knowledge,” the researchers wrote, “We have investigated and presented the functional entities of the architecture and interworking procedure in optical network automatic operation. The performances are demonstrated on the testbed for intent-based control. Our experiments verify that IDON with SAGO can effectively perform intent translation and zero-touch configuration.”

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On Feb 3, medical workers at Wuhan Pulmonary Hospital in the central province of Hubei welcomed a new “comrade”, one who had no fear of the novel coronavirus even though he wasn’t wearing protective clothing － a robot designed to deliver medication and meals.

“Please wear masks and wash your hands frequently during this special period. Let’s conquer the difficulties together,” the robot intoned as it moved around the Department of Respiratory Medicine.

Li Ming, deputy director of the hospital’s information department, said the robot’s route is based on a map set by a computer programme.

Nurses bring meals for the 60 patients to the quarantine area and place them on the robot, which can deliver 10 to 15 in one journey, saving time and energy while also reducing human contact.

In a bid to save protective gear and prevent infections among medical workers, the hospital has launched an online system that allows doctors to check patients via video screens.

Meanwhile, an online diagnosis system has been built to support treatment in hospitals in Enshi and Xiangyang, both in Hubei, and the expert team at Wuhan Pulmonary Hospital has provided diagnoses for more than 30 patients via remote consultations.

UPGRADES

Faced with the epidemic, governments at all levels, tech companies and local communities are joining the battle against the coronavirus by upgrading the technological aspects of control and prevention work.

Last month, President Xi Jinping said the battle against the epidemic cannot be won without scientific and technological support, according to Xinhua News Agency.

On Feb 28, the Ministry of Science and Technology published a notice on its website encouraging businesses to deploy robots, temperature-screening machines and other devices that could help to reduce human contact as the nation returns to work following the enforced layoff after the Spring Festival Holiday.

Big data is being collected on platforms to monitor the development of the epidemic, while drones are being used to disinfect roads and open spaces. Meanwhile, temperature-screening technology and artificial intelligence are being employed in the detection and analysis of possible risks amid the gradual resumption of work.

Residents nationwide can trace the latest developments of the epidemic and obtain health tips from online sources, such as WeChat mini programs launched by internet companies like Tencent Holdings.

An epidemic map, locations of communities with confirmed cases and information to refute rumours are available on the monitoring platforms, which aim to provide people with accurate information in a timely manner.

Cities in Hubei, such as Xiangyang, Suizhou and Xiaogan, have built online platforms where people can report developments related to the epidemic, search their travel history to see if they shared planes or rail carriages with people who were later confirmed as having the coronavirus, and receive a remote diagnosis.

Led by the local governments of several cities in Hubei and the e-commerce giant Alibaba, these kinds of platforms facilitate control-and-prevention work in communities by ensuring that people returning from Wuhan are registered and placed under observation.

SOFTWARE SOLUTIONS

Alipay Health Code － smartphone software that indicates health status － was rolled out in more than 100 cities nationwide within a week of being introduced in Hangzhou, Zhejiang province, on Feb 11, according to Xinhua News Agency.

After people fill in a survey of their recent travel history, close contacts, temperature and related symptoms, they are assigned a code in green, yellow or red, depending on their suggested physical condition.

Those with green codes can freely enter or exit communities and workplaces, while those with red or yellow codes should enter a period of self-quarantine.

As of Feb 28, more than 15 million people in Zhejiang had registered with the system, which provides a visual indication of whether it is safe for them to return to work. “Have you turned green?” has become a popular catchphrase in the province.

NONHUMAN DELIVERIES

In addition to robots in hospitals, the e-commerce giant JD is deploying self-driving robots to deliver items to medical workers in Wuhan in a bid to protect both customers and employees.

The robots can easily cover the distance between the logistics point and a designated hospital, about 600 meters, according to the Shanghai Observer news portal.

Meanwhile, in some parts of the country, drones are being used to patrol open places, spray disinfectant and conduct thermal-imaging procedures.

Liu Shuai, a farmer in Mianzhu, Sichuan province, allowed the local village authorities to use a newly purchased agricultural drone to spray disinfectant.

“Drones are more convenient, and they can spray material more evenly than manual or electric devices,” he told Red Star News.

He volunteered to operate the drone and spray roads in his village at 9 am every morning. The work used to take a team a whole day to finish, but Liu completes the task in about three hours.

Meanwhile, a community official in Yichun, Jiangxi province, started a trend of using drones equipped with thermal-imaging technology to assess body temperatures, according to news portal Jiemian.

Yi Jinyu, who enjoys working with new technologies such as drones, 3D printing and data visualisation, bought the device from DJI, a leading provider of easy-to-fly drones.

During its 30 minutes of flight time per charge, the drone can detect temperatures ranging from -10 deg C to 140 deg C, thereby meeting all the demands for widespread inspections of people and goods in open spaces.

In January, Yi came up with the idea of deploying drones to assess temperatures.

After he started using the drone to gauge temperatures, many other communities quickly decided to follow suit.

On Feb 2, a community in Hangzhou started using the devices to conduct temperature checks in open spaces, such as parks.

If an individual registers a temperature reading that may indicate a fever, he or she is located by officials who conduct tests to ascertain the details of the situation and respond accordingly.

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Chinese autonomous vehicle startup Pony.ai said Wednesday that it has received a $400 million investment from Japanese automaker Toyota, upping the ante in its push to develop automated vehicles.

The Guangzhou-based company will use the fresh capital to boost the development and commercialization of driverless cars, which will mainly feature what’s called “Level 4 autonomy.”

The Society of Automotive Engineers divides autonomous driving technology into six levels ranging from 0 to 5. Level 4 autonomy allows a car to be in almost total control all the time without any human intervention.

The new investment marks an extension of the two companies’ partnership initially forged in August 2019, when Pony.ai and Toyota joined forces to conduct road tests of autonomous vehicles in Beijing and Shanghai using the Japanese automaker’s Lexus-branded cars.

According to a statement published on Pony.ai’s public WeChat account, the two partners will also explore a possible partnership on mobility services.

In 2018, Pony.ai started piloting its PonyPilot project in the southern city of Guangzhou, testing a fleet of 100 autonomous cars used for taxi-hailing.

Toyota is also a financial backer of Chinese ride-hailing giant Didi Chuxing. In July last year, the Japanese carmaker announced that it would invest $600 million in Didi and their new joint venture for mobility services. Didi also plans to test its robotaxi services in Shanghai this year.

Earlier this week, China’s National Development and Reform Commission and several other government agencies published an autonomous vehicle development plan, setting a goal for 2025, by which time the country should achieve mass production of vehicles with “conditional” self-driving capabilities.

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BEIJING: A man who had travelled to Wuhan — the central city at the heart of China’s coronavirus crisis — was surprised when police showed up at his door after he returned home, asking to check his temperature.

The man, who had quarantined himself at home in Nanjing, eastern Jiangsu province, said he had not told anyone about his recent trip to the city.

But by trawling through travel data from Wuhan, local authorities were able to identify him and dispatch officers to his home last week, according to a newspaper article posted by the Nanjing government.

As Chinese authorities race to contain the spread of a new virus, which has infected more than 34,000 people and killed more than 700 in China, Beijing is turning to a familiar set of tools to find and prevent potential infections: data tracking and artificial intelligence.

Several Chinese tech firms have developed apps to help people check if they have taken the same flight or train as confirmed virus patients, scraping data from lists published by state media.

In Guangzhou, southern Guangdong province, robots at one public plaza have even been deployed to scold passersby who are not wearing masks, according to the state-run Global Times.

And in Beijing, one neighbourhood committee responsible for an apartment complex of about 2,400 households said they used flight and train data to keep track of everyone’s recent travel record.

“Use big data technology to track, screen priority (cases), and effectively forecast the development of the epidemic in real-time,” China’s National Health Commission (NHC) told local governments in an online statement Tuesday.

“Strengthen the information link between…public security and transportation, and other departments,” it said, urging them to share train, flight, communication, and medical data.

As Chinese authorities search for potential infections, a point of focus has been detecting fevers, a common symptom of the disease.

While neighbourhoods and office buildings rely primarily on hand-held thermometers, public transport hubs are also trialling fever detection systems that use artificial intelligence and infrared cameras.

In Beijing, a system developed by Chinese search giant Baidu screens travellers at the Qinghe railway station using infrared and face detection technology, which automatically photographs each person’s face.

If someone has a body temperature of 37.3 degrees Celsius (99 degrees Fahrenheit) or above, the system sets off an alarm — prompting a secondary check by station staff.

On Thursday, railway personnel, clutching red-and-white megaphones, ordered passengers arriving from northern Shanxi province to slow down as they passed by Baidu’s system.

According to the company, its system can check more than 200 people a minute, far faster than the thermal scanners used at airports.

Megvii, an AI firm that was blacklisted by the US in October over alleged rights abuses, has developed a similar system, which is currently being used at a subway station in Beijing.

“Having a team of nearly 100 people working together remotely from home hasn’t been easy,” said a spokesperson at Megvii in an emailed statement.

“All of them are working around the clock during Lunar New Year public holidays,” said the company, adding that the team had to optimise its models to “effectively detect temperature with only the forehead exposed.”

Besides fever detection, Chinese tech firms have raced to develop a wide variety of services to help with epidemic control efforts, from preparing drone deliveries of medical supplies to mapping the spread of the virus from Wuhan.

Although the city has been under effective quarantine since January 23, some five million travellers left Wuhan during the Lunar New Year festival, according to the city mayor — galvanising a nationwide search for recent Wuhan visitors.

Still, the majority of tracking carried out by local authorities in China requires a lot of manpower, though some are entering data online to help with registration, especially as residents return after the holiday.

In Beijing, some neighbourhoods are prompting residents to scan a QR code to fill out personal details, such as their phone number and hometown address.

One form also prompted participants to fill out details on their mode of transport, such as their licence plate or flight number, if they had travelled.

It also asked if they had “recently” visited central Hubei province — where Wuhan is located — or come into contact with anyone from the hard-hit region.

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