Driven by the increasing demand for data, connectivity and automation, the amount of Internet of Things (IoT) devices continues to expand across consumer electronics and industrial applications. Integrating energy harvesting (EH) technologies as a battery-free alternative requires a controlled setting to emulate realistic EH systems. Yet, current tools are often not sufficiently accurate to model all hardware and software components of an EH system. Moreover, it is hard to mimic realistic energy availability scenarios, which are crucial for the design and optimization of EH systems. Therefore, a novel emulation platform is introduced that facilitates the development, testing, and optimization of complete and realistic EH systems. This emulator device replicates the behavior of the entire EH system. It consists of a Raspberry Pi 5 with a custom developed add-on hardware hat and dedicated software. This add-on hardware hat provides a stable output voltage between 1.2 and 3.6 V to the IoT device under test and contains a current measurement circuit with an accuracy of$0.6~\mu $A. The software includes novel and accurate digital-twin models of the energy harvester, the storage element, and the power management unit, enabling the emulation of various EH scenarios. Two application scenarios are demonstrated, a wireless bluetooth low energy (BLE) heart rate sensor optimized for ambient light EH and a compact wireless BLE temperature sensor optimized for radio-frequency EH. The proposed emulation platform enables rapid EH design evaluation under varying energy conditions, streamlining development and validating system reliability. This could be an important step toward establishing EH as a sustainable and widely adopted alternative to conventional battery-powered systems.

Industrial wireless sensor networks offer a viable alternative to wired solutions where there is a lack of suitable communication infrastructure. Among these networks, time slotted channel hopping (TSCH) emerges as a noteworthy choice due to its 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 article introduces a novel 6TiSCH low-power node (6LPN) that supports ultralow-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 6TiSCH friend node (6FN), ensuring an 87%–94% reduction in power consumption during operational mode while maintaining an average latency of queued frames of 7.62 s. By comparing the impact of the optimizations on three Internet of Things (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.

A batteryless Internet of Things (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 cannot be used to assess if IoT devices can be powered by energy harvesters. Therefore, this article 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 nonnegligible impact on the communication requirements. Finally, we discuss how to apply the model to other technologies and other use cases.

Wireless Sensor Networks (WSNs) operating in unlicensed frequency bands or employing battery-less devices, require a Duty Cycle (DC) limit to ensure fair spectrum access or limit energy consumption. However, in multi-hop networks, it is up to the network protocol to ensure that all devices comply with such DC restrictions. We therefore developed a distributed DC adherence algorithm that limits the DC of all devices without introducing any additional packet overhead. This paper presents a brief description of the algorithm and evaluates its performance through simulation. Our results show that the algorithm can limit the DC of all devices to ensure no devices must switch off. Our algorithm therefore provides a solution for WSNs where nodes must operate below a DC limit.