A battery-less IoT offers a sustainable alternative to battery-powered IoT devices, which produce billions of dead batteries every year. Devices are instead powered by a small supercapacitor, which is recharged by a renewable energy source. However, since IoT devices are often characterized by intermittent periods of high energy consumption followed by periods of reduced activity, conventional average energy consumption models can not be used to assess if an IoT devices can be powered by energy harvesters. Therefore, this paper presents an alternative feasibility evaluation approach that focuses on modeling the worst-case periods with peak energy consumption and short idle times, which pose the highest constraints on the capacitor’s behavior. This approach simplifies the characterization of the wireless technology energy consumption as these worst-case periods can be determined by a few parameters. The methodology is then applied to combinations of popular IoT technologies (LoRaWAN, BLE Mesh, and 6TiSCH) and energy sources (solar, kinetic, and radio frequency energy) for two common IoT use cases. We show that the proposed parameters can be successfully extracted with power measurements for different network configurations and that the Power Management Unit configuration has a non-negligible impact on the communication requirements. Finally, we discuss how to apply the model to other technologies and other use cases.

The progress in cm-accurate ultra-wideband localization systems encourages the adoption on larger scales. To calculate the distance between a mobile tag and anchor nodes with known locations, a two-way-ranging (TWR) scheme is often used where the time-of-flight (TOF) is determined by exchanging at least two packets. This TWR scheme avoids the need for synchronization between devices to compensate for clock drift. However, in TWR systems, mobile tags continuously need to decide with which anchor nodes to range. Currently, most scientific papers assume the tag ranges sequentially with all anchor nodes, thereby limiting the scalability. In addition, precious time is wasted trying to range with anchors that encounter poor channel characteristics. This letter proposes two novel anchor selection algorithms that tackle both problems. Anchors are selected in real-time based on their link quality, improving accuracy by selecting the best-performing anchor nodes. The algorithms are based on heuristic methods to estimate the link quality and the corresponding ranging error. The algorithm's two variants are evaluated in a realistic dynamic industrial setup, reaching an accuracy up to 15 cm. This represents a 50% improvement compared with ranging with all available anchors.

Industrial Wireless Sensor Networks (IWSNs) using the 6TiSCH standard offer a scalable, cost-effective alternative to wired solutions in industrial environments, especially in hard-to-reach areas. Mains-powered devices face high installation costs and cable vulnerabilities, while battery-powered devices are limited by lifespan and maintenance challenges. Energy harvesting and supercapacitors offer promising alternatives with longer lifetimes and reduced maintenance. However, only battery-less end devices are usually considered. Due to the intermittent energy availability of battery-less devices and demanding network requirements, routers are assumed to be continuously powered. Therefore, this paper proposes, to the best of our knowledge, the first solution to integrate battery-less routers into 6TiSCH networks, building on previous work that used real-time traffic prediction models. We extend this by developing an energy consumption and storage prediction mechanism, enabling adaptive scheduling based on a node’s available energy. The proposed adaptive algorithm dynamically modifies the Time Slotted Channel Hopping (TSCH) Scheduling Function to reduce the energy consumption of battery-less routers while triggering topology changes to ensure network reliability and adaptively route data based on dynamic energy availability. Evaluation of the algorithm in both small- and large-scale topologies demonstrates its effectiveness in reducing energy consumption and improving network performance by dynamically adjusting timing schedules. This approach significantly enhances the reliability and uptime of battery-less networks, although it introduces latency. Overall, the solution advances the development of fully energy-autonomous IWSNs, suitable for non-critical building automation and similar applications.

While the ongoing fourth industrial revolution continues to be a major driver behind wireless communication technologies, some environments are so prohibitive that even state-of-the-art solutions can barely achieve ubiquitous wireless connectivity (if at all). For example, in industrial sites with large metal constructions (such as petrochemical plants), highly localized and time-varying changes in wireless link quality are quite common. Oddly enough, much of the capabilities needed to deal with such effects are already present at the physical layer (PHY), but remain largely unexploited by higher protocol layers. In fact, little Industrial Internet of Things (IoT) (IIoT) research has considered harnessing the full multi-modal capabilities of modern multi-PHY/multi-band IoT hardware in general. As such, in this vision paper, we: (1) analyze recent advances towards enabling multi-modal IIoT through link- and routing layer operations; and (2) describe challenges and opportunities for future IIoT deployments, based on the design choices that emerged from said analysis. In summary, we identify a combination of a modified/extended Time-Slotted Channel Hopping (TSCH) link layer, using either fixed or variable duration timeslots, together with a Parent-Oriented (PO) Routing Protocol for Low-Power and Lossy Networks (LLNs) (RPL) approach to be the most promising way forward.

Industrial wireless sensor networks offer a viable alternative to wired solutions where there is a lack of suitable communication infrastructure. Among these networks, TSCH emerges as a noteworthy choice due to their capacity for deterministic latency, heightened reliability, and low power consumption. Nonetheless, challenges arise from the energy-intensive joining procedure and inherent idle listening associated with TSCH, impeding the integration of battery-powered end devices. Therefore, this paper introduces a novel 6LPN that supports ultra-low-power operations. The proposed solution optimizes the energy-intensive joining procedure through reduced advertisement channels, optimal scanning time, and a delayed join, achieving a 90% reduction in energy consumption. Furthermore, idle listening is eliminated by queueing downlink traffic in a 6FN, ensuring an 87-94% reduction in power consumption during operational mode while maintaining an average latency of queued frames of 7.62 seconds. By comparing the impact of the optimizations on three IoT hardware platforms, we demonstrate that optimal results are obtained for devices with low RX and idle transceiver current. Finally, our solution maintains full backward compatibility with 6TiSCH and does not introduce additional control traffic.