Written by Álvaro Capell and David Bonomo
The recent media explosion of the metaverse concept has overshadowed another technological trend, augmented or mixed reality, which is transforming the way we relate to the physical world, and which, as it is expected to evolve in the coming years, will bring about a revolution in many areas at both the individual and social levels.
This mixed reality, in addition to the technologies that are currently under rapid development to integrate the visual interface in overlap with the physical world, is based on two fundamental pillars for the digitisation of the physical: on one hand, it is necessary
1) to sensor the environment and objects to enable interaction with them, and on the other, it is necessary
2) to deploy a layer of intelligence to ensure that this interaction is relevant and adds value. This is where the combination of Internet of Things (IoT) and Artificial Intelligence (AI) is critical to make this vision a reality.
In this digitised world, vertical solutions are not isolated, but leverage the data generated by other solutions to improve the accuracy of their algorithms and deliver more valuable business outcomes. It is this combination of sources that makes the tandem of IoT and AI, AI of Things, so powerful and potentially applicable to a multitude of verticals and sectors:
One of these is smart buildings or smart building, where the proper exploitation of data from a multitude of solutions used in building management (room booking, access and capacity control, energy efficiency management, dynamic digital marketing, space sanitisation…) provides the possibility of integrating and unifying this information in dashboards that allow a building manager to quickly understand what is happening and act accordingly. Likewise, the use of Machine Learning or Deep Learning algorithms in these scenarios can contribute to more efficient and sustainable management, through use cases such as predicting the building’s energy consumption based on visitor patterns and other external factors such as weather forecasts, or adjusting environmental parameters according to the levels of traffic at any given time.
Another example, within the world of retail analytics and smart spaces, is the combination of data from outdoor location analytics tools with data generated inside the shop through video or wifi analytics and digital signage solutions, which provides a wide range of new AI functionalities for retailers to exploit. These include the possibility of guaranteeing end-to-end traceability of the sales funnel within the establishment or the recommendation of the most appropriate marketing content to display on screens according to the type of audience that is visiting them at any given time.
It is also worth noting the natural fit of the AI of Things concept in areas as relevant as smart metering and Industry 4.0. In the former, the information captured through smart meters in real time provides utilities (water, gas or electricity) with various options to enhance the use of Big Data to reduce losses, such as the detection of anomalies that lead to the early detection of potential fraudulent behavior. In the second, new technologies such as 5G or Edge Computing have enabled the huge and rapid capture of large volumes of data that allow, among other things, the development of predictive maintenance algorithms for industrial machinery (through information from sensors) or the identification of flaws in certain spaces (through data provided by a drone, for example) to facilitate maintenance work on electricity grids or solar panels in a building.
Finally, it would be important not to overlook the wide range of applications that AI of Things brings to the field of connected mobility, where data such as mileage, speed, consumption or driving habits, generated through a device connected to a vehicle’s OBD port, can feed different analytical models that enable transport companies to manage their fleets more efficiently. Likewise, within this field, the role played by the data provided by different asset tracking technologies (BLE, RFiD, WiFi…) is also decisive for, on the one hand, ensuring end-to-end visibility of the logistics value chain, and on the other, making certain predictive and prescriptive applications feasible, aimed at optimising inventory or maintaining the cold chain, among other options.
At Telefónica Tech IoT & Big Data we continue to deepen the concept of AI of Things by developing innovative solutions such as those briefly described in this article. The following articles in this series will provide a detailed description of each of these solutions at both a business and technical level.