Smart Logistics Thanks to Precise Positioning and IoT

To deliver orders by courier or to ship goods, commodities and materials via the railroad network, IoT technologies make reliable and efficient logistics possible.

In 2021, delivery companies handled over 4.5 billion parcels, courier and express items in Germany, according to the industry association Bundesverband Paket & Express Logistik (BIEK). Deutsche Post DHL alone delivered 1.8 billion parcels from door to door. These numbers explain why autonomous solutions such as delivery robots to make last mile logistics easier and more effective are such a fast growth market. The last mile is, of course, the final stage of delivery to the customer. Nationwide use of autonomous delivery vehicles is still only the shape of things to come, but companies all over the world are already working on systems of this kind. By 2027 their market volume is forecast to increase to around USD 50 billion from about $12bn in 2020.

The last mile is the one that poses logistics challenges. Roads are often narrow and congested in downtown areas, making it difficult to deliver parcels on time. The sheer number of shipments is a further contributory factor. Yet smooth and timely delivery is the key to customer satisfaction, and in case of doubt negative experiences reflect badly not only on the logistics provider but also on the supplier. Autonomous solutions can simplify last mile delivery but they present problems of their own such as difficulties with navigation. That is where the Internet of Things (IoT) can remedy the situation with Precise Positioning, as demonstrated by the UK company Level Five Supplies.

Level Five Supplies is currently developing a delivery robot that reliably negotiates sidewalks and helps to optimize the logistics. The problem is that detailed sidewalk maps are often not available. Obstacles and bends also make route planning and navigation more difficult, as do space limitations. Classical positioning solutions like the GNSS (Global Navigation Satellite) systems GPS in the U.S. or Galileo in Europe lack the necessary precision. The robot must not just take the shortest route to its destination; it must also not collide with obstacles and be damaged.

To overcome these challenges Level Five Supplies tested the Precise Positioning navigation solution on a delivery robot using a PGM (Precise GNSS Module) evaluation platform. Precise Positioning, from Telekom and Swift Navigation, relies for one on GNSS position data and for another on data provided by the Cloud-based Skylark correction service. This combination accounts for Precise Positioning’s high level of precision. Hundreds of measuring stations on different continents continuously monitor satellite navigation malfunctions. The resulting correction data makes GNSS data more precise. IoT hardware and GNSS receivers on the robot receive both sets of signals – normal position data and corrections – and conflate them. Swift’s Starling positioning engine delivers the precision required. Precise Positioning is accurate to within a few centimeters, compared with the 3 to 15 meters of GPS or Galileo.

Level Five Supplies was convinced by the result of the IoT technology. The robot had no difficulty in negotiating the test run with the precision required. The use case demonstrates how precisely the company tested Precise Positioning, which challenges had to be overcome and which specific benefits the technology provides for Level Five Supplies.

In addition to exact positioning Precise Positioning offers it and other logistics enterprises further benefits, such as low energy consumption and an attractive return on investment. The technology is also easily scalable and highly suitable for mass production, a valuable advantage in view of the rising number of last mile deliveries. For 2022 the retail trade association Handelsverband Deutschland (HDE) anticipates over € 97 bn of online business in Germany, or around  €11 bn more than last year – and that will mean more parcels to deliver.

The last mile is not all that there is to logistics, however. Merchandise, products and other goods, for example, must first be transported from the producer to the distributor or to the processor. Rail transportation is one of the main modes. According to Germany’s Federal Statististics Office goods totaling over 357 million tonnes were shipped by rail in 2021. Railroad network outages upset the supply chain and can swiftly lead to economic damage. To prevent that a German company, PANTOhealth GmbH, has developed an infrastructure monitoring system. Using live monitoring, predictive data evaluation and artificial intelligence (AI) in the software, it calculates possible outages in advance, making predictive track maintenance possible. So the ideal time for maintenance and repairs can be established.

Critical places in the railroad network must be located precisely if the maintenance teams are always to know exactly where their deployment location is. Using conventional GNSS systems that is not easy, especially if two error locations are close to each other. On the lookout for a better solution, PANTOhealth incorporated a Precise Positioning evaluation kit in its existing system. In practice the advantages of Precise Positioning were quickly apparent. With positioning accurate to within 10 cm, PANTOhealth can set a precise position in its system for every error location. That improves processes and saves time because the maintenance team knows exactly where to go.

PANTOhealth concluded that Precise Positioning enables it to maintain the railtrack network more easily and more efficiently, delivering both reliability and safety benefits. For further details on how PANTOhealth uses Precise Positioning see the use case.

Be it on the last mile or at an earlier stage in the supply chain, using smart IoT technology for precise positioning is a factor that paves the way for Smart Logistics (see box). And many other companies in different industries use Precise Positioning to improve their performance and their services. For insights see both Parts 1 to 4 of the blog’s Precise Positioning series and the corresponding use cases.