To ensure that COVID-19 pandemic protocols are followed for the safety of passengers and staff, the GMR Hyderabad International Airport (GHIAL) has implemented Queue Management Systems (QMS). The QMS integrates Internet of Things (IoT) security cameras and artificial intelligence (AI) video analytics that help to improve and manage passenger movement. This will reduce crowds at passenger touchpoints such as the check-in counters, security check-ins, immigration, baggage carousel, etc.
According to a news report, the GHIAL has collaborated with AllGoVision Technologies to ensure that the project is implemented smoothly. The QMS uses a camera-based video analytics technology that will continuously observe passenger movements on a few key parameters such as peak passenger waiting time or key zones where there is excess crowding. It will enable authorities to take corrective actions to overcome such issues. This will be a corrective step to safeguard passengers and airport staff.
Deep learning-based AI models will support advanced video analytics to accurately measure passenger behaviours over time. The combo-technology will also help in enhanced security measures at the GHIAL such as camera tampering, loitering, parking violations, object classification, wrong-way detection, and left object detection. An official noted that GHIAL has adopted a slew of safety measures to ensure passengers feel safe when they transit through the airport. With this smart queue management technology, security, and safety takes the airport experience one notch higher and creates passenger confidence while ensuring seamless operations. Leveraging the artificial intelligence/machine learning technology, the detailed Queue Management solution aids in providing accurate business intelligence for managing people at the airport entrance, service counters, security booths, and immigration counters.
India has been using AI in several other areas to fight COVID-19. For instance, the Centre of Artificial Intelligence and Robotics, under the Defence Research and Development Organisation, has developed an AI-based intelligent COVID detection application software ATMAN AI. The intelligent web-based software can classify images under ‘normal’, ‘COVID-19’, and ‘pneumonia’, using chest X-rays, a report explained.
ATMAN AI is powered by a Deep Convolutional Neural Network. The software pre-processes the images before passing them to the neural net to take care of the variant illuminations levels of the X-Ray images. ATMAN AI can be accessed using mobiles, tablets, laptops, or computers. DRDO claimed ATMAN AI had shown an accuracy of 96.73% on digital chest X-rays of RT-PCR-positive patients. So far, ATMAN AI has been tested and validated by doctors from the HCG Centre for Academics and Research and Ankh Life Care, in Bengaluru.
Further, the Indian Institute of Technology in Kharagpur (IIT-K) launched COVIRAP, a diagnostic tech to detect infectious diseases such as COVID-19. COVIRAP consists of a pre-programmable control unit, a special detection unit on genomic analysis, and a customised smartphone app to display the test findings. IIT-Ropar developed a first-of-its-kind IoT device called AmbiTag. The device records real-time ambient temperature during the transportation of perishable products, body organs, blood, and vaccines, etc. AmbiTag is a USB-shaped device that continuously records the temperature of its immediate surroundings from -40℃ to 80℃ in any time zone for a full 90 days on a single charge. As OpenGov Asia reported, the AmbiTag temperature data log advises the user whether the transported item is usable, or the cold chain has been compromised during the transportation.