Can artificial intelligence revolutionise the logistics sector?

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While AIoT isn’t without its disadvantages – many processes will lose their human element and become completely autonomous, which could lead to job losses – it has numerous advantages when it comes to improving productivity, optimising resources, and reducing expenses.

Enhanced operational efficiency with AIoT

As Ryan Gaines, CEO of City Logistics (a leading privately-owned logistics company in South Africa), explains, AIoT makes intelligent processing possible. “AIoT systems are not only connected, they’re also smart enough to make decisions and predictions. This results in significantly enhanced operational efficiency within logistics,” he explains.

For instance, AloT can provide predictive analytics for maintenance, meaning it will forecast when a vehicle might require maintenance before it breaks down. AIoT can also power autonomous delivery vehicles and drones, and enable them to select their most efficient routes.

Furthermore, AIoT can be used in automated warehouses where AI-driven robots handle tasks such as picking, packing, sorting, and storing goods. “Using data collected from Internet of Things (IoT) devices across the supply chain, it can also predict future demands more accurately,” comments Gaines

Overall, AIoT has the potential to transform many operations in logistics. “The establishment of City Tech, our associate company specialising in technology development, is constantly looking for ways and means to implement new technology innovations with AI being the latest technology development ” comments Gaines.

AIoT implementation challenges

In a South African context, while many companies incorporate the Internet of Things (IoT) into processing and systems, in order for AIoT systems to operate efficiently, data quality and availability are paramount.

The efficacy of AI systems inherently hinges upon the quality of the input data they receive. These systems depend on precise, comprehensive, and current information to render accurate forecasts and decisions. Flawed input data could compromise the AI system’s outputs, leading to misdirected deliveries, improper resource allocation, or faulty customer communications.

Considering these AIoT technologies are a relatively new innovation, another significant hurdle for AIoT implementation involves the considerable initial investment necessary to procure requisite technology and provide adequate staff training.

The race is on to master the application of this technology within the operational landscape of South Africa - the benefits are simply too big to ignore.