We propose a novel approach to measure photosynthetically active radiation (PAR ) in the form of photosynthetic photon flux density with an inexpensive, small multi-channel spectrometer sensor, with integrated optical filters and analog-to-digital converter. Our experiments prove that the combination of eight spectral channels with different optical sensitivities, such as the sensorchip in use (AS7341, ams), derive the PAR with an accuracy of 14/$\mathrm{m}$${}^2$/$\mathrm{s}$. Enabled by the sensor architecture, additional information about the light quality can be retrieved which is expressed in the RLQI. A calibration method is proposed, and exemplary measurements are performed. Moreover, the integration in a solar-powered wireless sensor node is outlined, which enables long-term field experiments with high sensor densities and may be used to obtain important indexes, such as the GPP.

In this paper we show that RF transmissions using the physical layer of the “Long Range” (LoRa^®) interface, and with some limitations also the data link and network layer Long Range Wide Area Network (LoRaWAN), are suitable even for extremely power-restricted devices, like energy-autonomous wireless sensor nodes (WSNs), if configured well. We analyse the most critical parameters and their influence on the power performance. This includes the outer circuitry, software and configuration of the transmitter SX1276 and the new SX1262. Based on that, we give specific advice to lower their power consumption and verify the impact of these measures with evaluations on an own build low power sensor node.

In this paper, we describe a novel animal-tracking-system, solely powered by thermal energy harvesting. The tracker achieves an outstanding 100 $\mathsf{\mu }\mathrm{W}$ of electrical power harvested over an area of only 2 times $20.5$$\mathrm{c}$$\mathrm{m}$${}^2$, using the temperature difference between the animal’s fur and the environment, with a total weight of 286 $\mathrm{g}$. The steps to enhance the power income are presented and validated in a field-test, using a system that fulfills common tracking-tasks, including GPS with a fix every 1.1 $\mathrm{h}$ to 1.5 $\mathrm{h}$, activity and temperature measurements, all data wirelessly transmitted via LoRaWAN at a period of 14 $\min$. Furthermore, we describe our ultra low power design that achieves an overall sleep power consumption of only 8$\mathsf{\mu }\mathrm{W}$ and is able to work down to temperature differences of $0.9$$\mathrm{K}$ applied to the TEGs.

The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is essential for understanding and modeling ecological processes. However, its continuous monitoring using manual state-of-the-art measurement instruments is still challenging. To address this challenge, we present an innovative sensor concept to obtain the LAI based on the cheap and easy to integrate multi-channel spectral sensor AS7341. Additionally, we present a method for processing and filtering the gathered data, which enables very high accuracy measurements with an nRMSE of only 0.098, compared to the manually-operated state-of-the-art instrument LAI-2200C (LiCor). The sensor that is embedded on a sensor node has been tested in long-term experiments, proving its suitability for continuous deployment over an entire season. It permits the estimation of both the plant area index (PAI) and leaf area index (LAI) and provides the first wireless system that obtains the LAI solely powered by solar cells. Its energy autonomy and wireless connectivity make it suitable for a massive deployment over large areas and at different levels of the tree crown. It may be upgraded to allow the parallel measurement of photosynthetic active radiation (PAR) and light quality, relevant parameters for monitoring processes within tree canopies.

In this paper, we present the design, set-up and testing of a fully energy-autonomous wildlife tracking collar that is supplied by thermoelectric energy harvesting from the animal's body heat. Attached to the neck of a mammal, the device determines the animal's activity, body-temperature and its own energy state. The data is then transmitted in regular short beacons which are also used for triangulation of the animal position. The characterization in laboratory and a field test show that the system design with an ultra-low power switch and a low-voltage step-up-converter with over 42 % efficiency is capable to measure and transmit continuously in intervals of 25 s.

This paper focuses on the design of an optimized thermal interface for a thermoelectric energy harvesting system mounted at endothermic animals. In this application scenario the mammal’s fur reduces the heat flux from the animal’s body through a thermoelectric generator (TEG) to the ambient air. This requires an adapted design of the thermal interface between TEG and body surface, to increase its thermal conductivity without harming the animal. For this purpose the thermal conductivity through a mammal’s fur is determined with a specially designed heatsink. An analytical model is built to predict the resulting thermal resistances and is validated with experimental results for two different fur lengths. We show that an optimized design of the thermal interface reduces its thermal resistance up to 38% compared to a trivial design while lowering its weight for about 23%. It is found that the most important design parameter of such a thermal connector is the ability to slide into the fur.