Investigation of Self-Powered IoT Sensor Nodes for Harvesting Hybrid Indoor Ambient Light and Heat Energy

Sensor nodes are critical components of the Internet of Things (IoT). Traditional IoT sensor nodes are typically powered by disposable batteries, making it difficult to meet the requirements for long lifetime, miniaturization, and zero maintenance. Hybrid energy systems that integrate energy harvesting, storage, and management are expected to provide a new power source for IoT sensor nodes. This research describes an integrated cube-shaped photovoltaic (PV) and thermal hybrid energy-harvesting system that can be utilized to power IoT sensor nodes with active RFID tags. The indoor light energy was harvested using 5-sided PV cells, which could generate 3 times more energy than most current studies using single-sided PV cells. In addition, two vertically stacked thermoelectrical generators (TEG) with a heat sink were utilized to harvest thermal energy. Compared to one TEG, the harvested power was improved by more than 219.48%. In addition, an energy management module with a semi-active configuration was designed to manage the energy stored by the Li-ion battery and supercapacitor (SC). Finally, the system was integrated into a 44 mm × 44 mm × 40 mm cube. The experimental results showed that the system was able to generate a power output of 192.48 µW using indoor ambient light and the heat from a computer adapter. Furthermore, the system was capable of providing stable and continuous power for an IoT sensor node used for monitoring indoor temperature over a prolonged period.

Cellulose Nanocrystal-Based All-3D-Printed Pyro-Piezoelectric Nanogenerator for Hybrid Energy Harvesting and Self-Powered Cardiorespiratory Monitoring toward the Human-Machine Interface

Biomaterials with spontaneous piezoelectric property are highly emerging in recent times for the generation of electricity from mechanical energy sources that are amply available in nature. In this context, pyroelectricity, an integral property of piezoelectric materials, might be an interesting tool in harvesting thermal energy from the fluctuations of temperature. On the other hand, respiration and heart pulse are the significant human vital signs that can be used for early detection and prevention of cardiorespiratory diseases. Here, we report an all-three-dimensional (3D)-printed pyro-piezoelectric nanogenerator (Py-PNG) based on the most abundant and completely biodegradable biopolymer on earth, i.e., cellulose nanocrystal (CNC) for hybrid (mechanical as well as thermal) energy harvesting, and interestingly, the NG could be used as an e-skin sensor for application in self-powered noninvasive cardiorespiratory monitoring for personal healthcare. Notably, the CNC-based device will be biocompatible and economically advantageous due to its biomaterial-based supremacy and huge availability. This is an original approach with 3D geometrical advancement in designing a NG/sensor, where the unique all-3D-printed manner is adopted, and certainly, it has promising potential in reducing the number of processing steps to required equipment during the multilayer fabrication. The all-3D-printed NG/sensor shows outstanding mechano-thermal energy harvesting performance along with sensitivity and is capable of accurate detection of heart pulse as well as respiration, whenever and whichever required without the need of any battery or an external power supply. In addition, we have also extended its application in demonstrating a smart mask-based breath monitoring system. Thus, the real-time cardiorespiratory monitoring provides notable and fascinating information in medical diagnosis, stepping toward biomedical device development and human-machine interface.

Energy Conversion Analysis of Multilayered Triboelectric Nanogenerators for Synergistic Rain and Solar Energy Harvesting

The triboelectric nanogenerator (TENG) is an emerging technology that offers excellent potential for the conversion of mechanical energy from rain into electricity for hybrid energy applications. However, a high-performance TENG is yet to be achieved because a quantitative analysis method for the energy conversion process is still lacking. Herein, a quantitative analysis method, termed the "kinetic energy calculation and current integration" (KECCI) method, which significantly improves the understanding of the mechanical-to-electrical energy conversion process, is presented. Based on the KECCI method, a high-performance TENG is developed by systematically optimizing a biomimetic surface structure and instant switch design, with 1.25 mA short-circuit current (I_sc ), 150 V open-circuit voltage (V_oc ), and a high energy-conversion efficiency of 24.89%. Furthermore, a multilayered TENG device is proposed for continuously harvesting the kinetic energy of raindrops for further improvement in the energy-conversion efficiency. Finally, the multilayered TENGs are integrated with organic photovoltaics, achieving all-weather energy harvesting. This work presents a validated theoretical basis that will guide further development of TENGs toward higher performances, which will promote the commercialization of hybrid TENG systems for all-weather applications.

Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review

Nowadays, wireless sensor networks are becoming increasingly important in several sectors including industry, transportation, environment and medicine. This trend is reinforced by the spread of Internet of Things (IoT) technologies in almost all sectors. Autonomous energy supply is thereby an essential aspect as it decides the flexible positioning and easy maintenance, which are decisive for the acceptance of this technology, its wide use and sustainability. Significant improvements made in the last years have shown interesting possibilities for realizing energy-aware wireless sensor nodes (WSNs) by designing manifold and highly efficient energy converters and reducing energy consumption of hardware, software and communication protocols. Using only a few of these techniques or focusing on only one aspect is not sufficient to realize practicable and market relevant solutions. This paper therefore provides a comprehensive review on system design for battery-free and energy-aware WSN, making use of ambient energy or wireless energy transmission. It addresses energy supply strategies and gives a deep insight in energy management methods as well as possibilities for energy saving on node and network level. The aim therefore is to provide deep insight into system design and increase awareness of suitable techniques for realizing battery-free and energy-aware wireless sensor nodes.

Portable Trilayer Photothermal Structure for Hybrid Energy Harvesting and Synergic Water Purification

Many exciting developments have unfolded on the recently emerged research topic of solar-driven interfacial evaporation, which is a promising technology for water purification. However, the sole heat source, i.e., solar energy, has put a limit on the maximum achievable evaporation rate. Therefore, to boost the evaporation beyond the limit, we here in this work have put forth a new photothermal system with a trilayered structure (TLS) that is capable of simultaneously harvesting hybrid energy in addition to solar energy for enhanced evaporation. A carbon-based material with broad-band light absorption that can be facilely synthesized through dehydration effect is also reported. Demonstrations of TLS evaporator by recovering the free thermal energy from sources like ground surficial heat and waste heat from laboratory facility and building walls together with solar radiation have been carried out. A remarkable synergic evaporation rate exceeding 2.4 kg m^-2 h^-1 is achieved, and moreover, the hybrid heating makes evaporation independent of solar intermittency. Besides, a TLS integrated hybrid water-purification bottle with outstanding portability is further demonstrated, which is expected to be of great significance to the development of mobile water purification and safe water security in the future.

Energy-Efficient Online Resource Management and Allocation Optimization in Multi-User Multi-Task Mobile-Edge Computing Systems with Hybrid Energy Harvesting

Mobile Edge Computing (MEC) has evolved into a promising technology that can relieve computing pressure on wireless devices (WDs) in the Internet of Things (IoT) by offloading computation tasks to the MEC server. Resource management and allocation are challenging because of the unpredictability of task arrival, wireless channel status and energy consumption. To address such a challenge, in this paper, we provide an energy-efficient joint resource management and allocation (ECM-RMA) policy to reduce time-averaged energy consumption in a multi-user multi-task MEC system with hybrid energy harvested WDs. We first formulate the time-averaged energy consumption minimization problem while the MEC system satisfied both the data queue stability constraint and energy queue stability constraint. To solve the stochastic optimization problem, we turn the problem into two deterministic sub-problems, which can be easily solved by convex optimization technique and linear programming technique. Correspondingly, we propose the ECM-RMA algorithm that does not require priori knowledge of stochastic processes such as channel states, data arrivals and green energy harvesting. Most importantly, the proposed algorithm achieves the energy consumption-delay trade-off as [O(1/V),O(V)]. V, as a non-negative weight, which can effectively control the energy consumption-delay performance. Finally, simulation results verify the correctness of the theoretical analysis and the effectiveness of the proposed algorithm.