INTELLIGENT BRANDS // Enterprise Security

Project Dartmouth will utilise Pangiam ’ s technologies alongside Google Cloud ’ s Artificial Intelligence ( AI ) and Machine Learning ( ML ) computer vision tools , such as their Vertex AI Platform . This technology will be tested within the security facilities of AGS Airport Ltd , owners and operators of Aberdeen , Glasgow and Southampton Airports in the UK .

Alexis Long , Chief Strategy Officer for Pangiam , said : “ This technology marks a monumental step in bringing automation to aviation security and sets a new precedent for international security standards . First and foremost , the technology will deliver a better experience for the traveller , the airport and governments . To help us achieve this , we have selected Google Cloud as our technology vendor of choice-a leader in Artificial Intelligence and cloud technologies .”

Mark Palmer , Head of EMEA Public Sector , Google Cloud , said : “ We are delighted to collaborate with Pangiam on this groundbreaking initiative to protect AGS ’ s network of passengers and customers . The power of Artificial Intelligence is boundless and we look forward to improving the aviation industry at large .”

Commenting on the announcement , Chief Operating Officer of AGS Airports Ltd , Mark Johnston , said : “ Google Cloud and Pangiam are world leaders in the Artificial Intelligence field and we are pleased to be working in partnership with both organisations on a cutting-edge project that could have a transformative effect on the security of our passengers and colleagues .” p

The collaboration means that Pangiam ’ s national security-grade technology and deep experience of managing aviation security threats will , for the first time , be boosted by Google Cloud ’ s industry-leading suite of AI technologies .

Project Dartmouth is intended to make air travel safer by integrating AI into airport baggage security and screening operations . The technology will in the first instance be focused on rapidly identifying potential threats in baggage , providing increased throughput at security checkpoints , addressing critical friction points in air travel as well as supporting security teams . In later phases the technology will scale to help tackle other pressure points in security and wider airport operations .

AI and ML models will be trained to be able to detect prohibited items in real-time as bags pass through airport X-ray scanning equipment . It will also be used to spot anomalies and unusual patterns which could indicate a new or co-ordinated attempt to breach security , before alerting security staff to examine those items further .

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