High precision positioning, low power wide area (LPWA), short range mesh networks, and edge intelligence promise to extend the range of applications for the IoT in the food sector and beyond.
If data is a primary driver of industrial digitalization, the technologies used to gather, transmit, store, and process it are its key enablers. This is also true in the food sector. From the farm, field, or plantation, through the entire supply and production chain, to retail – even into our homes – digitalization is always about the acquisition of data, analytics at the edge or on the cloud, and leveraging the data to optimize development. Improvements in the quality of the data and the technologies used to gather, transfer, and analyze it typically translate into improved processes. In some cases, however, they can enable entirely new applications, opening brand new markets.
The latest generation of high precision positioning technology is doing just that, leveraging multi-band GNSS (Global Navigation Satellite Systems) combined with GNSS correction data. By dramatically bringing down the cost of ownership of the technology, high precision positioning is not only becoming accessible to a broader market, it is also paving the way for the development of new autonomous solutions. Whether they are autonomous agricultural vehicles or unmanned delivery drones, the small, lightweight, and low-cost high precision positioning technology robustly delivers positioning accuracies down to a few centimeters. Is it disruptive? It will be a game changer.
The cost of cellular data transmission and hardware have long been bottlenecks for the deployment of extensive wireless sensor networks. Offering enhanced geographical coverage, low-cost hardware and data plans, as well as over 10 years of battery life in some use cases, the latest generation of licensed low power wide area networks, including LTE-M and Narrowband IoT (NB-IoT), are quickly brushing aside these limitations. Applications such as crop monitoring, livestock monitoring and fleet tracking will be among the first to benefit from these technologies.
Mesh networks offer a way to efficiently scale up wireless sensor networks by having individual nodes relay messages across the network, thereby expanding their reach and enabling wide-ranging applications from irrigation net- works to smart processing plants to connected supermarkets. Standardized platforms such as Bluetooth® mesh ensure that devices remain interoperable, even if they come from different suppliers. And by including nodes capable of transmitting information using mobile communication networks – forming so-called capillary networks – mesh networks can be extended to enable cloud based applications.
Because of the massive amounts of data they generate, many IoT applications would run into a bottleneck: bandwidth. Edge computing, yet another technological innovation, offers one solution to that problem. Rather than streaming all of the gathered data to the cloud for analysis, smart sensors, gateways, or a local server take over some of the analytics, only transmitting an aggregate value, such as an average, an alert, or a message to the cloud. Machine learning algorithms run on the “edge” – i.e. before data is sent to the cloud – can detect outliers and other abnormal behavior the farmer, plant manager, or store manager should be aware of.
Read more on the IoT of Food in the u‑blox U magazine.