AI for Efficiency: Bangalore Airport Integrates Computer Vision-Based Artificial Intelligence Platform
One of the advantages of artificial intelligence is its ability to see what is going on in ways that humans simply cannot. As an example, as part of attempts to curb illicit fishing, Google employs AI and satellite data to observe the world's fishing fleets at work overall 1.4 billion square miles of Earth's oceans. The same ability to see and then make sense of noisy, complex data can be utilized to design and manage improved aircraft boarding procedures. Instead of the current parade of inefficiencies, AI-powered computer vision might aid in the design of just-in-time, queue-less experiences. The current connection between ground transit and air travel in both directions is far from perfect. See the curbside traffic jams at any major airport's arrivals and departure lanes for proof. Alternatively, many airports are still figuring out how to deal with the development of ride sharing, such as where to put waiting drivers and how to restore lost revenue from parking.
Delta's work with US Customs and Border Protection has already executed the opening of the first biometric airport terminal. At least for first- and business-class passengers, similar technologies are currently in place at Dubai International Airport. While innovative, these artificial intelligence-powered solutions are early examples of the emerging technological change in airport and airline operations. They are developing excursions into artificial intelligence throughout the passenger experience. Technology will play a role in some of these endeavors; society will have intelligent and adept instruments for independently managing massive complexities and achieving new efficiencies. Another factor will be new competitive pressures; with autonomous vehicles offering tempting alternatives to flying, the future of air travel will necessitate significant changes.
Bengaluru International Airport Ltd Integration Artificial Intelligence (AI)
Bengaluru International Airport Ltd announced the integration of the former's computer vision-based artificial intelligence (AI) platform into the airport's operations in collaboration with local computer vision business Industry.ai and US tech firm Nvidia Corp. The firms announced in a joint statement that the technology will be used at Bengaluru Airport's Terminal 2, which began international operations on August 31.
The airport will utilize the video analytics and AI platform to follow queues at various checkpoints across the terminal, analyze and resolve congestion, track abandoned baggage, and alert security officers in the event of suspicious movements. To accomplish this, the platform will connect to video feeds from 500 live cameras across Terminal 2, which will then be connected to Industry.ai's data analytics portal, which can provide up to 12 outcomes based on the video feeds. These outcomes will include indicators for spotting bottlenecks as well as safety problems, such as overspeeding or suspicious vehicle movement outside the airport terminal.
Industry.ai, a subsidiary of private green energy firm Bharat Light & Power, has built its vision AI platform on the Nvidia Metropolis development suite, which provides businesses with a ready-to-use platform for building video feed-based data analytics solutions.
According to Tejpreet Chopra, CEO of Industry.ai, “the platform will accelerate passenger flow during peak hours of operation." The company plans to spread its service to other airport terminals as well. Bengaluru International Airport Limited's chief information officer, George Fanthome, confirmed that the platform was "a first" for any airport terminal.
The deployment at Bengaluru's new international terminal coincides with the latter becoming one of the first in the country to use the Centre-backed facial recognition travel approval software, DigiYatra. It was developed by Hyderabad-based Data Evolve Solutions and supported by the Union Civil Aviation Ministry, which currently operates across seven airports, including Delhi, Kolkata, and Bengaluru.
However, just as the introduction of DigiYatra prompted privacy and data collecting concerns, experts believe that a terminal-wide vision AI platform may do the same.
Abhishek Malhotra, managing partner at Delhi-based TMT Law Practice, says, “Concerns may be made about how such a tool would manage personal data, especially how the relevant authorities would obtain agreement from transiting passengers to gather and use their data. In light of the Digital Personal Data Protection Act, the consent procedure may be necessary to consider.”
Other factors that may be crucial include how the data is acquired and how it is discarded.
The recently notified DPDP Act may prove significant in specifying the precise implications of handling and mishandling of persons' physical and biometric data—which are classified as personal data. However, Malhotra cautioned that the Act has yet to specify how the Data Protection Board will handle such issues.
Stitching Together the Winged and the Wheeled
AI's strength is struggling with complex issues and then discovering novel solutions, which is one of the reasons several artificial intelligences have already defeated the best human players at board games like chess and Go. AI is highly equipped to solve intricate machinations and movements within an airport because of its ability to produce new moves based on a practiced grasp of numerous prior actions. The current connection between ground transit and air travel in both directions is far from perfect. See the curbside traffic jams at any major airport's arrivals and departure lanes for proof. Alternatively, many airports are still figuring out how to deal with the development of ride sharing, such as where to put waiting drivers and how to restore lost revenue from parking.
If AI can be used to shift passengers from one mode of transportation to another by effectively controlling everyone as it moves on a game board, it may also be able to change the laws of the game for some passengers.
AI's ability to learn new maneuvers might be leveraged to provide better experiences for some passengers while providing less ideal experiences for others. How could this be? Consider that we are a species with a long history of racism, misogyny, ageism, and other forms of discrimination. Those same biases could inadvertently or deliberately find their way into the artificial intelligence we design and administer, ushering in a kind of invisibly managed discrimination. Members of one faith may be given preferential treatment in one airport while feeling unwelcome in another.
Passengers aboard airport-operated cars may find themselves oddly arranged by race. People who comply with perceived gender standards in their appearance may be rewarded with faster throughput, whereas others confound the system, causing delays that effectively operationalize everyday social evils. Of course, many individuals are already familiar with this form of discrimination. However, the benefits of air travel are its ability to connect the world and its people, so AI working against that value would be a particularly disturbing conclusion.