The Use of Smart Surveillance Technologies for Suicide Prevention in Public Spaces: A Professional Stakeholder Survey from the United Kingdom

Joyner, L., Cliffe, B., Mackenzie, J.-M., Pettersen, E., Philips, P., Marsh, I. and Marzano, L. Forthcoming. The Use of Smart Surveillance Technologies for Suicide Prevention in Public Spaces: A Professional Stakeholder Survey from the United Kingdom. BMC Public Health.

TitleThe Use of Smart Surveillance Technologies for Suicide Prevention in Public Spaces: A Professional Stakeholder Survey from the United Kingdom
TypeJournal article
AuthorsJoyner, L., Cliffe, B., Mackenzie, J.-M., Pettersen, E., Philips, P., Marsh, I. and Marzano, L.
Abstract

Background
Around a third of suicides in the United Kingdom occur in public spaces, such as on the railways, at bridges, or coastal locations. Increasingly, the use of Artificial Intelligence and other smart technologies are being proposed as a means of optimising or automating aspects of the surveillance process in these environments. Yet relatively little is known about how they are being used for suicide prevention and the realities of deploying these systems in public spaces.
Methods
108 professional stakeholders across the UK completed an online survey to understand how smart surveillance technologies are being deployed across different types of public spaces to (also) prevent suicides. Through a series of multiple choice and open-ended questions, participants were also asked about the perceived benefits, limitations, and biggest barriers of implementing these technologies for suicide prevention reasons.
Results
72 examples of smart surveillance technology were identified, with around two-thirds at “high-risk” locations. Motion-activated CCTV, cameras with AI analytics, and Automatic Number Plate Recognition (ANPR) cameras were the most commonly identified technologies. More than half of systems alerted a control room when activated, and the majority (80%) initiated a human-led response.

JournalBMC Public Health
ISSN1471-2458
PublisherSpringer
Web address (URL)https://www.researchsquare.com/article/rs-5137455/v1

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