Tiny batteryless Internet of Things (IoT) devices that depend on the harvested energy from their environment provide a promising alternative for a sustainable IoT vision. These devices use small capacitors as energy storage, which together with the unpredictable and dynamic harvesting environment results in intermittent on–off behavior of the device. The crucial issue to effectively use batteryless IoT devices is to find a way of enabling the successful execution of application tasks in face of this intermittency. As the conventional computing models cannot handle this behavior, in this article, we present an energy-aware task scheduler for batteryless IoT devices based on dependencies and priorities, which can intelligently schedule the application tasks avoiding power failures and maintaining forward progress. With the properly defined voltage thresholds for each application task, using our energy-aware task scheduler a safer execution can be ensured. We evaluate our approach based on emulated and real experiments and validate it using two types of power management units (PMUs) (environment emulator and intelligent PMU based on the AEM10941 chip). Our results show that the energy-aware task scheduler is able to react and adapt the execution to environmental changes, avoiding power failures. Comparing to the state-of-the-art scheduling approaches, which are mostly not aware of the energy, we show that our energy-aware task scheduler can keep the device on during the full time of the experiment, executing more tasks when a relatively small capacitor of 10 mF or less is used at harvesting currents as low as$40 ~\mu \text{A}$.

Many IoT scenarios, such as smart cities, wild life monitoring, or smart agriculture, involve thousands of battery-powered devices. The disposal and replacement of such batteries represent an important economical and environmental cost. To realize Green IoT solutions, it is therefore desirable to adopt battery-less energy-neutral devices that can harvest power from renewable sources, such as solar or wind energy and store it in much more sustainable capacitors. The limited and inconstant energy supply and the limited energy storage capacity of such devices, however, require special care in the design of communication and computational processes, which have a major impact on the energy consumption of the devices. In this work, we explore multiple elements that could affect the device energy and communication capabilities of LoRaWAN devices. We propose and compare different energy-aware packet transmission algorithms, and test them in a scenario where values for the harvested power are collected from real testbeds. We show that the number of successfully transmitted packets can be doubled by using an energy-aware design approach.

Tiny energy harvesting battery-less devices present a promising alternative to battery-powered devices for a sustainable Internet of Things (IoT) vision. The use of small capacitors as energy storage, along with a dynamic and unpredictable harvesting environment, leads these devices to exhibit intermittent on-off behavior. As the traditional computing models cannot handle this behavior, in this demo we present and demonstrate an energy-aware task scheduler for battery-less IoT devices based on task dependencies and priorities, which can intelligently schedule the application tasks avoiding power failures.

Bluetooth Low Energy (BLE) is emerging as an Internet of Things (IoT) technology that effectively connects small devices and sensors. It can enable many smart building use cases such as automation and control, environmental condition monitoring, and indoor location services. The BLE mesh standard provides a friendship feature to support Low Power Nodes (LPNs). We demonstrate how these BLE LPNs can support communication (uplink, downlink, or bidirectional) when powered by ambient indoor light using a mini solar panel and a small capacitor for energy storage. Being batteryless, it can exhibit intermittent behaviour with periodic ON and OFF states. However, with the knowledge of the capacitor voltage, an energy-aware LPN can try to avoid the OFF state. It can delay the execution of upcoming tasks by switching to an SLEEP state (consuming minimum energy) and provide some time to recharge the capacitor. We consider an example use case of monitoring temperature and room occupancy. The mesh nodes in the network can send instructions (such as turn-on an LED or a buzzer) to the batteryless LPN that should be executed by it. We study the use-case with real experiments on the communication feasibility of an energy-aware BLE LPN in a network and characterize the capacitance behaviour by placing a 6 W light bulb at 120 cm from the solar panel.

Narrowband Internet of Things (NB-IoT) is becoming one of the most promising low-power wide area (LPWA) networking technologies. It can support more than 50 000 devices within a cell using licensed spectrum. NB-IoT provides low energy consumption, reliable connectivity and deep indoor coverage for the device, making it a good candidate for IoT use cases. NB-IoT introduces two novel energy-saving techniques, namely, extended discontinuous reception (eDRX) and power saving mode (PSM). This article presents a Markov chain model to evaluate the power consumption and latency of NB-IoT devices using PSM and eDRX. By exploiting the characteristics of the steady-state distribution of the Markov chain, the probabilities in steady-state can be obtained explicitly. Based on these probabilities, we calculate the system downlink (DL) latency as a function of different timers of these power-saving features. We also compare the model to simulation results obtained from the ns-3 event-based network simulator, to determine its accuracy. The results show that its performance in terms of energy and latency is comparable. Our model is accurate with consideration of the protocol details and the new radio resource control (RRC) Idle features of NB-IoT. The results show that the analytical model achieves an average accuracy of more than 91% for power consumption and DL latency. Lastly, we use the model to automatically determine the optimal parameter set in terms of latency and power consumption for various IoT use cases with different traffic requirements, based on multiobjective analysis of the Pareto front.

The Internet of Things (IoT) already connects billions of devices and keeps growing exponentially. These devices are designed to be integrated with industrial machines, home appliances, and infrastructures. One such use case is to build a smart grid management system that relies on demand-response techniques to control the appliances automatically so that the power can be distributed optimally. The mission-critical smart grid communications require secure, reliable, two-way communicable, and latency bounded connections between the management system and the electrical appliances. To realize these, cellular technology is arguably the most feasible solution. 3GPP has already released the narrowband-IoT (NB-IoT) standards as the low-power dense-area coverage IoT cellular solution. In this article, we present an NB-IoT system to monitor and control the connected electrical appliances in a smart grid network. The platform is also capable of configuring the network dynamically. We assess the latency performance for our solution using the commercially available Orange network in Belgium. It is observed that NB-IoT enabled devices can be controlled and monitored with a maximum latency less than 8 s in the deep-indoor environment and within 2 s for the outdoor environment.

Narrowband Internet of Things (NB-IoT) is gaining prominence as a key Low Power Wide Area Network (LPWAN) technology for IoT applications. Since it operates on licensed frequency spectrum it can provide guarantees to applications demanding Quality of Service (QoS). NB-IoT has emerged as a competitive rival for other LPWAN technologies such as LoRa and Sigfox, which work in the unlicensed frequency spectrum and are vulnerable to interference. Therefore, NB-IoT is the trivial fit for industries and other business companies that demand guaranteed services. In this paper the different features of the NB-IoT technology have been studied on the commercial Orange network in Belgium using the ublox SARA-N210 module [1] as the user equipment (UE). We focused on the device and network performance in terms of setup times, signal quality, throughput, latency, and reliability and studied the network dynamicity on signal strength. These observations are then compared with the theoretical defined limits of NB-IoT.