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AI for workplace safety and productivity: how does it fit?

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Even with safety regulations and procedures in place, accidents and incidents remain a regular occurrence and continue to be a major challenge for employers, in almost all industries, across the globe. The future outlook of moving towards an AI-enabled future is here. Today, certain domains under AI come into play that can predict accidents and mishaps slightly before they occur.

The advent of COVID pandemic has catalysed the adoption of AI amongst businesses. As most businesses are under the pump to respond effectively to the post-COVID-19 environment, they aim to take all possible positive steps to maintain the safety and well-being of their workforce. However, the challenge is to manage workplace safety and productivity with their existing portfolio of assets, in some cases with even fewer resources and budget. In such a scenario, knowing how workplace safety can be enhanced with AI can be helpful for most employers.

AI provides us with more data and intelligence than ever before, and our ability to utilise this data could enhance business operations manifold. There is a subdomain of artificial intelligence (AI) called computer vision that is best used for workplace safety and productivity management.

The computer vision technology has allowed for greater understanding of work environments and even reducing accidents by a significant margin. It can also be integrated into manufacturing maintenance, quality and production systems to alert workers when they need to check a machine or perform a quality check.

So how does it work and is it easily implemented?

Most people are familiar with CCTV cameras, they are omnipresent and quite practical for a range of different industries. The computer vision technology analyses live video feeds from these cameras using deep learning and neural networks. It then triggers alarms according to the use case it’s trained for – such as identifying PPE or face mask noncompliance, social distancing, damage, pilferage, oil spillage, fire, potential fall of a heavy object from height, unauthorised entry in restricted areas, and so on.

It can generate hidden insights on efficiency in terms of space utilization, MHE utilization, machine utilization, etc. while keeping an eye out for damage and pilferage – be it manufacturing premises or a warehouse, computer vision can analyse the whole environment and generate relevant insights. It only depends on the use case it is trained for.

Alarms are raised via WhatsApp, push notifications, or to a control room, along with an image and location making it easier to pinpoint where the incident may have taken place and to enable a faster response.

It can bring benefits in terms of cost reduction, improved efficiency and advanced workplace safety. Data insight is key for understanding the risks of workplaces and efficiency of various machines, assets and workforce. It enables better risk management decision-making.

Lastly, the ability to monitor occupational fatigue or hazardous environments more efficiently can be a huge value addition for both the workers and the employer.

Implementing this technology is easy and scalable as it works with any existing CCTV infrastructure and provides the potential for minimising, or even preventing, workplace incidents and injury while measuring the efficiency and productivity of man, machine, and space without a bias.

The post AI for workplace safety and productivity: how does it fit? appeared first on NASSCOM Community |The Official Community of Indian IT Industry.

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