Edge artificial intelligence (edge AI) is a system that uses machine learning algorithms to process data that is generated by a local hardware device (the edge) to make independent decisions in real-time – without having to connect to the cloud or the internet.
By Pramod Venkatesh, group chief technology officer of inq
Edge AI is already so prevalent in our day to day lives, it seamlessly integrates into applications such as speech recognition in smart speakers, facial recognition in banking platforms, and real-time traffic updates on our smartphones.
And, while there are many uses in place already, the market for edge AI software is expected to grow in value to $1,12-trillion by 2023 (from $355-million in 2018). The future applications for edge AI are virtually limitless – including use in hospitals for the analysis of medical images in emergency care, in autonomous vehicles through increased real-time localised processing, and to enhance safety and process compliance in manufacturing facilities.
The current state of security and the opportunity for edge AI
Within the realms of security, edge AI has a critical role in enabling organisations and individuals to act quickly to threats.
While the benefits of edge AI are clear – including real-time analysis, predictive modelling, real-time alerts and notifications – many organisations often do not have the knowledge to implement new systems or software. This results in a continued state that is limited by finite manpower and outdated systems that struggle to stay ahead of advancing criminal activity.
By utilising existing equipment and resources to gather data, edge AI algorithms identify and predict suspicious behaviour, improving efficiencies without the need to overhaul your entire existing security system.
Applications of edge AI in security
Using edge AI to track and monitor loitering or suspicious behaviour in high-traffic areas, such as malls, enables security teams to act on potential situations before they escalate.
A notification that arises from the analysed data means that teams are proactive and able to prioritise resources – instead of trying to monitor hundreds of closed circuit television (CCTV) screens and reacting once an event has occurred.
Shop owners who have experienced stock losses can track and predict behaviour – including tracking and stopping individuals who visit certain areas of the store and leave without checking out.
Through an edge AI implementation, advanced analytics that uses facial recognition, customised behavioural predictions, and tracking, will enable security interventions at an earlier stage.
Edge AI is the future of security
Edge AI, at its core, can take hours of footage and convert that to data. Thousands of hours of footage can be reduced to data with patterns – that are analysed in real-time. The capacity of edge AI to create and analyse this information to continually drive data-driven business decisions is unlimited.
With the ease of integration, and the utilisation of existing technology, edge AI is a complementary addition that improves the sustainability of organisations looking to improve security and make informed decisions faster – without the need to increase headcount or completely change existing systems.
Embrace edge AI for sustainable change
As the world evolves, so does our technology. As things become more and more complex, there is even more data that is available to assess. And while humans are needed for the assessment and action of these data cues, edge AI is vital to simplify the masses of data into usable and actionable insights.
Organisations looking to make sustainable technological changes in security should embrace all the applications that edge AI has to offer, which is adding value quickly and effectively.