According to a survey, unplanned downtime across manufacturing setups can result in losses of over $260,000 per hour. What follows is inevitable disruptions and a sense of helplessness in the face of destabilized operations. Ultimately, this depletes a business’s resources, hinders employee productivity, delays time-to-market, and results in the loss of customer trust.

Elsewhere, shoplifting is now a $100 billion problem in the retail sector, as revealed by the 2022 National Retail Security Survey (NRSS). The survey further outlines how 47.4% of the respondents experience cargo theft when the products are en route from the distribution centers (DCs) to stores. In fact, 31.6% affirm having experienced theft at DCs itself.

The situation is even more dire on the human security front. As per the data released by International Labor Organization (ILO), more than 340 million workplace accidents are observed across the world every year. This results in about 2.3 million men and women getting victimized.

In a broader sense, all these problems across manufacturing, retail, oil and gas, construction, etc., revolve around the same fundamental issue — the lack of a seamless flow of timely, relevant, and accurate information. But why’s that the case?

The Problem of Post-Mortem Analysis

Today, we have cameras everywhere – from our pockets to street corners, manufacturing facilities, retail stores, etc. They record much of the happenings around us in real time. With all this data, it’s a wonder why there aren’t many high-profile, widely prevalent issues that have been resolved by leveraging the information obtained. That’s because these installations don’t add value, or perhaps their value isn’t realized in a way that can help prevent future problems.

The fact is that most of the time, the visual data captured isn’t being analyzed at all. It’s either used for post-mortem analyses, i.e., after an issue, or a collection of issues, has entirely transpired and caused a crisis, or as a laggard incident reporting mechanism. For example, a lot of times, security personnel are glued to the screens at certain fixed intervals of the day, and a call center is set up to receive inputs on the occurrence of an issue if any. This is certainly not enough in an era where:

• An increased footfall across stores is invariably desired
• Every day, millions of products are being moved
• The need to be economical while handling logistics is evergreen
• Downtime is an immediate threat to quality control, productivity, and operational costs
• Shoplifting, pilferage, etc., is rampant across the globe
• The need to be attentive to customer needs is more stringent than ever
• Security culture is an integral part of customer satisfaction
• Every second counts, and there is an expectation of proactive action

How a Visionary Computer Vision Platform Approach Can Help Solve these Issues

In the face of all these issues, a forward-looking computer vision (CV) platform can prove to be a game changer.

Consider this; a lot of data is captured every minute across a variety of channels. For example, a manufacturing facility will have system data and IoT data at its disposal. This traditional system data and digital sensory data, in combination with visual data, can help paint a clear picture of what’s happening on the ground. Computer vision technology, which employs deep learning and neural networks, can train the machine on this data, curate deep learning models to accommodate machine vision, and eventually discern the anomalies and their source. 

But how is it different from human vision? Although computer vision requires immense training of machines on relevant data, it can analyze the environment (and thousands of assets within) at an incredibly rapid pace. Plus, this processing is nearly impeccable. Given this accuracy, the computer vision platform can cue people to act at the earliest opportunity to nip a potential crisis in the bud.

More profoundly, here’s how a CV platform like KamerAI can prove to be a key enabler across a broad spectrum of use cases.

Security

A CV platform can detect and prevent shoplifting, pilferage, etc. It can also help secure perimeters by leveraging real-time CCTV data to identify a trespasser or an attempted breach and alert the authorities about the same.

In addition to this, a computer-vision-based analytics tool can leverage facial recognition to reduce the need for biometric scanning or access cards when entering a facility. Hard hat detection is yet another application of such an intelligent platform, which can assist in ensuring a safe working environment.

Operations

Be it associated with capturing accurate dimensions of products, monitoring industrial machinery, identifying unattended objects, tracking freight usage, detecting logistical damages, inspecting product quality, etc., a CV platform in place can prove to be an exceptional tool for operational optimization. It can go beyond just providing end-to-end visibility into a facility’s activities by empowering businesses to make rational decisions.

Prediction

Since machine vision models are trained on a lot of data, they are able to identify patterns and trends that could be the source of anomalies transpiring down the line. For example, KamerAI helps perform predictive maintenance by alerting the concerned about which machines are prone to an impending breakdown. This allows businesses to plan ahead and execute preventive measures.

The Way Forward with a Robust Computer Vision Platform

The introduction of a computer vision platform can help improve the overall product quality, drive operational efficiency, ensure worker safety and adherence to compliances, prevent theft and perimeter intrusion, and avoid operational issues. 

Across industrial facilities, supply chains, and retail stores, such a platform can allow businesses to leverage the power of “autonomous anything.”

Interested in installing a CV platform to ramp up on-site supervision and increase operational productivity? Get in touch for a personalized demo.