This work describes an experimental study on the possibilities of harvesting energy from tree trunks in order to power sensor nodes for environmental monitoring, particularly in wild forests. As the trunk of a living tree can be divided into isothermal subvolumes, which are generally referred to as annual rings, and the trunk is a good heat storage material, depending on the tree dimensions and its species, it can potentially offer different temperature gradients according to the tree trunk depths. The hypothesis is to consider the application of this temperature gradient on the faces of a Peltier cell to obtain electrical energy. In order to evaluate this hypothesis, a wireless sensor network was developed for measuring internal temperature of trunks from different trees. The experimental results show that it is possible to obtain a sufficient temperature gradient to harvest energy from tree trunks. Additionally, it is also shown that it is possible to harvest thermal energy during the day and during the night while photovoltaic cell only works under sunlight.

Energy harvesting is an emerging area with a wide range of low-energy applications and consists of capturing very small amounts of energy from one or more naturally-occurring energy sources (e.g. solar, thermal, wind, kinetic, etc.), accumulating and storing them. Recently, energy harvesting based on magnetic induction is gaining more and more attention because of their promising performance in power grid since energy can be harvested by the wasted magnetic field around power line using the principle of electrical transformer. However, the performance of the induction-based harvester presents very different results according to the magnetic core material used. In this work, it is presented experimental results on induction-based harvester considering the power density achieved by different magnetic core materials.

In recent decades, expansion in urban areas has faced issues such as management of public waste, noise, mobility, and air quality, among others. In this scenario, Internet of Things (IoT) and Wireless Sensor Network (WSN) scenarios are being considered for Smart Cities solutions based on the deployment of wireless remote sensor nodes to monitor large urban areas. However, as the number of nodes increases, the amount of data to be routed increases significantly as well, meaning that the choice of the data routing process has great importance in terms of the energy consumption and lifetime of the network. In this work, we describe and evaluate the energy consumption of routing protocols for WSN-based Smart Cities applications in LoRa-based mesh networks, then propose a novel energy-saving radio power adjustment (RPA) routing protocol. The Cupcarbon network simulator was used to evaluate the performance of different routing protocols in terms of their data package delivery rate, average end-to-end delay, average jitter, throughput, and load consumption of battery charge. Additionally, a novel tool for determining the range of nodes based on the Egli propagation model was designed and integrated into Cupcarbon. The routing protocols used in this work are Ad Hoc On-Demand Distance Vector (AODV), Dynamic Source Routing (DSR), and Distance Vector Routing (DVR). Our simulation results show that AODV presents the best overall performance, DSR achieves the best results for power consumption, and DVR is the best protocol in terms of latency. Finally, the proposed RPA routing protocol presents power savings of 11.32% compared to the original DSR protocol.

As solar radiation is the most plentiful energy source on earth, thermoelectric energy harvesting emerges as an interesting solution for the Internet of Things (IoTs) in outdoor applications, particularly using semiconductor thermoelectric generators (TEGs) to power IoT devices. However, when a TEG is under solar radiation, the temperature gradient through TEG is minor, meaning that the TEG is useless. A method to keep a significant temperature gradient on a TEG is by using a solar absorber on one side for heating and a heat sink on the other side. In this paper, a compact TEG-based energy harvester that features a solar absorber based on a new class of solid matter, the so-called quasicrystal (QC), is presented. In addition, a water-cooled heat sink to improve the temperature gradient on the TEG is also proposed. The harvester is connected to a power management circuit that can provide an output voltage of 3 V and store up to 1.38 J in a supercapacitor per day. An experimental evaluation was carried out to compare the performance of the proposed QC-based harvester with another similar harvester but with a solar absorber based on conventional black paint. As a result, the QC-based harvester achieved 28.6% more efficient energy generation and achieved full charge of a supercapacitor around two hours earlier. At last, a study on how much the harvested energy can supply power to a sensor node for Smart agriculture during a day while considering a trade-off between the maximum number of measurements and the maximum number of transmission per day is presented.

Biosensors are a type of sensor that have gained prominence in recent years due to their advantages over traditional sensing methods, which are expensive and time-consuming. They are composed of two main parts: a recognizer bioelement and a transducer—both can be of different types depending on the desired application. An optical biosensor based on Surface Plasmon Resonance (SPR) achieves high sensitivity, is label-free and its multilayer construction allows an increase in the selectivity of the target analyte. As the choice of layers in SPR-based biosensors and the analysis of the obtained multilayer configuration is very difficult and expensive, in this work, we present an SPR-based biosensor simulation tool, developed through mathematical modeling, with an easy-to-use interface and several design options for calculating and analyzing the reflectance and angle of incidence of this type of device. The application, developed in Matlab, behaved as expected, offering the user the possibility to export data to Excel and becoming a useful alternative for mathematical analysis of SPR biosensors and its parameters, such as quality factor, detection accuracy and sensitivity.

The vast and rising problems related with electric energy generation predominantly produced from fossil fuels, such as carbon dioxide emission and air pollution, demand a constant search for development of new renewable energy technologies. In this context, Energy Harvesting can be characterized as the harvesting and storage of portions of available energy in an environment. A Thermoelectric Module (TEM) can operate as an electrical generator and as a cooling/heating device since it can be used for conversion between thermal and electrical energy. A TEM is a valuable device for thermal-based energy harvesting systems. When working as electrical generator, a TEM is a denominated Thermoelectric Generator (TEG), and the generated electric energy is proportional to the temperature gradient on the faces of the device, known as the Seebeck effect. For cooling/heating applications, a TEM is a denominated Thermoelectric Cooler (TEC). It works as a heat pump, since, by applying an electrical current into the TEC, the generated heat flows from one side of the device to the other, known as the Peltier effect. Thereby, one side of the module will be heated while the opposite will be cooled simultaneously.