Computer Vision

Millions of dollars are lost every year across sectors due to tools, equipment, and other assets going missing, and many hours are spent by workers searching for them. Computer vision technology can provide useful solutions to help track such assets and save time and money.

When a worker picks up a wrench and walks around a facility with it, a computer that processes connected visual feeds can locate where the wrench was last put down, while also tracking dozens of other tools at the same time. Vehicles like forklifts in a warehouse or trucks in a yard can also be tracked; this data can be used to determine if vehicle movements are performed in an optimal way. Furthermore, visual AI software can follow pallets of goods in inventory sections and keep accurate records of shelf vacancies and how long a pallet has remained on a shelf, in addition to tracking any falling or shifting parcels in the back of courier vans.

In implementing computer vision solutions in their facilities, logistics providers can avoid wasting time searching for misplaced assets and manually confirming asset locations. They can also use the analyses from visual AI to further optimize operations and accurately determine inventory stock levels.

Maintaining and improving safe working conditions is a top priority for the logistics industry. The COVID-19 pandemic increased attention to this and visual AI technology will be relevant and helpful to workplace safety in the years ahead.

During the peak of the pandemic, computer vision was used to ensure workers adhered to personal protective equipment (PPE) regulations. At DHL, we now see this technology expanding into other workplace safety use cases. Cameras and the AI behind them may one day detect if employees are utilizing ergonomic best practices to minimize injury risk, identify lone-worker emergency situations in less-trafficked areas, ensure vehicles are complying with local speed limits, and even determine if predefined walking pathways are being respected in a facility.

To ensure personal and data privacy, advanced computer vision solutions can blur out faces or separate personal identifying factors from analyses. This is helpful as it demonstrates to all parties that the goal of computer vision is not finding fault with individual workers but ensuring their safety and optimizing the workplace experience by assessing workflows, mapping out areas of high incidences, and triggering process change.

With today’s global supply chain networks strained and under immense pressure, logistics operations must remain functional and unhampered by incidents and broken-down equipment. Computer vision can help with this.

Digital side mirrors like those designed by Israeli startup Brodmann17 can highlight nearby vehicles, especially those in blind spots, to truck drivers, enabling safer lane changes and turns while also reducing incident risk. Meanwhile, visual AI via cameras, whether on gates or drones, can detect irregularities in various objects like airplane wings, shipping containers, and warehouse rooftops, initiating predictive maintenance procedures to assess any potential damage or need for repair. Computer vision can also be applied to repair or emergency stocks, keeping inventory count, flagging items like lubricants and spare wheels that are running low, and triggering timely replenishment.

With computer vision as a preventative tool, logistics organizations can better protect supply chains from avoidable delays.