This paper presents the implementation of a wearable wireless sensor network aimed at monitoring harmful gases in industrial environments. The proposed solution is based on a customized wearable sensor node using a low-power low-rate wireless personal area network (LR-WPAN) communications protocol, which as a first approach measures CO₂ concentration, and employs different low power strategies for appropriate energy handling which is essential to achieving long battery life. These wearables nodes are connected to a deployed static network and a web-based application allows data storage, remote control and monitoring of the complete network. Therefore, a complete and versatile remote web application with a locally implemented decision-making system is accomplished, which allows early detection of hazardous situations for exposed workers.

This work presents a low-rate wireless personal area network-based sensor network for early detection and monitoring of forest fires. The system has been designed to perform different parameter measurements at different tree heights, depending on the forest relief. Thereby, it is possible to know how fire affects the soil mantle, stems and treetops, as well as to detect underground fires. Measures of power consumption confirm the feasibility of the implementation of this sensor network. Using a duty cycle of 0.33% and with the selected low-voltage-low-power compliant sensors, the network operating life is greater than one year.

This paper presents a wireless traffic flow detection system, mainly focused on conditions in which the traffic flow is slow or stopped, which increases the risk of highway accidents. To achieve this goal, a Low Power Wide Area Network (LPWAN) based on LoRa called Short LoRa has been developed. This LoRa sub-network complies with the European Telecommunications Standards Institute (ETSI) harmonized standard for its compatibility in Europe countries. In addition, the development of the devices has allowed them to also work on a LoRaWAN network. The introduced development has been compared to a reference system mounted with laser barriers that provided a high accurate comparison. Field tests of the system have been carried out and the data obtained in the measurement has been analyzed with two different methods, and both of them were valid for the application. The results can determine vehicle speed with adequate precision at low speeds. The attenuating behavior of the communication signal is also analyzed through the Radio Signal Strength Indicator (RSSI). The relationship between vehicle speed, gate distances and RSSI attenuation has been studied. The system is proven to have efficient results in detecting traffic flow under the conditions for which it has been developed.

The use of wireless sensor networks (WSN) for monitoring physical and chemical variables in large areas allows density and frequency measurements which have been unavailable to date in classical measurement systems. To fully take advantage of this technology in a particular application, besides an accurate design and selection of all the components involved in its operation, it is essential to dispose of reliable lifetime estimation prior to deployment. This paper presents an experimental approach to determine the actual lifetime of such battery-operated systems, making use of a custom WSN architecture, and for different batteries technologies. To render a reliable evaluation, the energy consumption of the sensor nodes under their different operation modes, in correlation with the battery characteristics and the voltage regulation system, is jointly considered. The result is a complete and practical lifetime model, whose appropriate performance has been validated in a real deployment scenario.

This paper presents an analysis of the lifespan of sensor nodes in a wireless network powered by batteries. For this, the energy requirements of the node electronics, sensors, radiofrequency data transmission protocols and the diverse energy modes have been considered. The characterization of the discharge profile for a battery with nominal 3.7 V output and 2Ah energy combined with the estimation of energy requirements of the selected node architecture show a general method for estimating the node behavior from the energetic point of view.

This paper presents a low-cost high-efficiency solar energy harvesting system to power outdoor wireless sensor nodes. It is based on a Voltage Open Circuit (VOC) algorithm that estimates the open-circuit voltage by means of a multilayer perceptron neural network model trained using local experimental characterization data, which are acquired through a novel low cost characterization system incorporated into the deployed node. Both units—characterization and modelling—are controlled by the same low-cost microcontroller, providing a complete solution which can be understood as a virtual pilot cell, with identical characteristics to those of the specific small solar cell installed on the sensor node, that besides allows an easy adaptation to changes in the actual environmental conditions, panel aging, etc. Experimental comparison to a classical pilot panel based VOC algorithm show better efficiency under the same tested conditions.