Remote real-time monitoring of subsurface landfill gas migration

Green IoT Event Detection for Carbon-Emission Monitoring in Sensor Networks

This research addresses the intersection of low-power microcontroller technology and binary classification of events in the context of carbon-emission reduction. The study introduces an innovative approach leveraging microcontrollers for real-time event detection in a homogeneous hardware/firmware manner and faced with limited resources. This showcases their efficiency in processing sensor data and reducing power consumption without the need for extensive training sets. Two case studies focusing on landfill CO2 emissions and home energy usage demonstrate the feasibility and effectiveness of this approach. The findings highlight significant power savings achieved by minimizing data transmission during non-event periods (94.8-99.8%), in addition to presenting a sustainable alternative to traditional resource-intensive AI/ML platforms that comparatively draw and produce 20,000 times the amount of power and carbon emissions, respectively.

Advanced IoT Pressure Monitoring System for Real-Time Landfill Gas Management

This research presents a novel stand-alone device for the autonomous measurement of gas pressure levels on an active landfill site, which enables the real-time monitoring of gas dynamics and supports the early detection of critical events. The developed device employs advanced sensing technologies and wireless communication capabilities, enabling remote data transmission and access via the Internet. Through extensive field experiments, we demonstrate the high sampling rate of the device and its ability to detect significant events related to gas generation dynamics in landfills, such as flare shutdowns or blockages that could lead to hazardous conditions. The validation of the device's performance against a high-end analytical system provides further evidence of its reliability and accuracy. The developed technology herein offers a cost-effective and scalable solution for environmental landfill gas monitoring and management. We expect that this research will contribute to the advancement of environmental monitoring technologies and facilitate better decision-making processes for sustainable waste management.

A Robust Miniaturized Gas Sensor for H2 and CO2 Detection Based on the 3ω Method

Gas concentration monitoring is essential in industrial or life science areas in order to address safety-relevant or process-related questions. Many of the sensors used in this context are based on the principle of thermal conductivity. The 3ω-method is a very accurate method to determine the thermal properties of materials. It has its origin in the thermal characterization of thin solid films. To date, there have been very few scientific investigations using this method to determine the thermal properties of gases and to apply it to gas measurement technology. In this article, we use two exemplary gases (H2 and CO2) for a systematical investigation of this method in the context of gas analysis. To perform our experiments, we use a robust, reliable sensing element that is already well established in vacuum measurement technology. This helix-shaped thin wire of tungsten exhibits high robustness against chemical and mechanical influences. Our setup features a compact measurement environment, where sensor operation and data acquisition are integrated into a single device. The experimental results show a good agreement with a simplified analytical model and FEM simulations. The sensor exhibits a lower detection limit of 0.62% in the case of CO2, and only 0.062% in case the of H2 at an excitation frequency of 1Hz. This is one of the lowest values reported in literature for thermal conductivity H2 sensors.

Environmental Monitoring Based on the Wireless Sensor Networking Technology

This paper investigates real-life environmental monitoring applications based on Wireless Sensor Networks (WSNs). Wireless sensor networking is an emerging technology, which through the research in the labs and the real deployments has proved to be a significant and valuable tool for scientists in their effort to explore various environmental phenomena. During the last decades, this wireless networking technology has been adopted by many scientific fields in order to accurately and effectively monitor climate phenomena such as air pollution, destruction phenomena (i.e., landslides), etc. It has also been widely used in agriculture as well as in horticulture for field monitoring. This paper provides a critical overview of the basic components existing WSN deployments use. It also categorizes these deployments, 111 in total, into five different field categories, namely agricultural monitoring, environmental monitoring, air-water pollution monitoring, monitoring of destruction phenomena, as well as monitoring of livestock, and wild animal, in order to provide a general view of the technologies used, the conditions under which the deployments were conducted, and much more. Then, five easy-to-use guides are provided discussing basic considerations for deploying WSNs in each of these fields. These guides cover various issues, such as sensor node platforms, operating systems (OSs), topologies, installation and maintenance issues, and much more. In order to showcase the usefulness of consulting the resulted guides, this work considers representative application scenarios for each of these field deployments.