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WAISL Introduces Digital Twin-Powered Integrated Airport Predictive Operations Centre

This is India's first end-to-end fully integrated digital twin-powered APOC that covers the Terminal, Airside and Landside, integrating with over 40 modules and tracking more than 100 KPIs, capable of managing 40+ million passengers annually. This isIndia'sfirst end-to-end fully integrated digital twin-powered APOC that covers the Terminal, Airside and Landside, integrating with over 40 modules and tracking more than 100 KPIs, capable of managing 40+ million passengers annually. WAISL's...
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This is India's first end-to-end fully integrated digital twin-powered APOC that covers the Terminal, Airside and Landside, integrating with over 40 modules and tracking more than 100 KPIs, capable of managing 40+ million passengers annually.

WAISL's innovative APOC solution can significantly benefit UK airports by enhancing operational efficiency, reducing flight delays, and improving passenger satisfaction. By integrating advanced technologies, airports can manage increased passenger volumes, optimise revenue streams, and reduce operational costs, ensuring a seamless and efficient travel experience.

This deployment ushers in a new era in airport operations, offering predictive, prescriptive, and simulative insights and a comprehensive 360-degree view of the entire airport ecosystem. The solution leverages next-generation technologies like Digital Twin, Cloud Computing, Computer Vision, AI/ML, video, and Data Analytics.

WAISL had identified and established a key partnership with Kloudspot using their IoT technology for this solution. More recently, WAISL partnered with AWS to further evolve this solution and take it to other airport and transport clients globally. This was launched by AWS via press releases and at their prestigious Re-invent in Las Vegas a few weeks ago. 

said

WAISL's digital solution is designed to deliver significant business advantages for airports. It  delivers real-time insights and an automated plan of the day that seamlessly integrates with all systems, predicts potential disruptions, analyses trends, and continuously learns from post-operative analysis for performance optimisation.

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The business value for airport operations by deploying the solution is derived by enhancing capacity with existing infrastructure, optimising non-aero revenue streams, and lowering costs through improved operational efficiency. The solution empowers airports to handle surges in demand with predictive and prescriptive analytics, ultimately delivering reductions in flight delays and boosting passenger satisfaction. It also provides a truly integrated experience that will fuel the next generation of airport operations, setting a new standard in the UK aviation industry.

At WAISL, we design, implement and integrate technologies with a focus on operations and process efficiencies for airports, airlines, smart cities, energy and hospitality. Our solutions—spanning biometric systems, digital twins, integrated command and control centres, cyber security/sustainability suites, predictive data-driven insights, etc. — work together seamlessly to deliver more innovative, efficient, and intuitive experiences, elevating business outcomes. 

WAISL is the primary solutions partner for Indira Gandhi International Airport, Delhi , Rajiv Gandhi International Airport, Hyderabad , Manohar International Airport, Goa , Bhogapuram International Airport, Kannur International Airport, and Kuwait International Airport. We manage and service 135+ million passengers and 80+ airlines, integrating and deploying 2000+ applications vendor-agnostically in highly complex technology-converging ecosystems. This excellence in managed services delivered by WAISL has enabled our partner airports to be rated amongst the best-in-class service providers by Skytrax and ACI awards.

Website: https://www.waisl.in


 

 

 

View original content: https://www.prnewswire.co.uk/news-releases/waisl-introduces-digital-twin-powered-integrated-airport-predictive-operations-centre-302334863.html

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