Optical Measurements Using LED Discharge Photometry (PEDD Approach): Critical Timing Effects Identified &amp; Corrected

Self Cite

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.

less power draw.…”

Section: Discussionmentioning

confidence: 99%

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

Fay,

Corcoran,

Diamond

2023

Self Cite

“…It must be noted that using an Op Amp in the LED-PD approach allows for temporal signal processing such as low/high/band pass filtering to account for noise and/or Fourier analysis—a process yet to be demonstrated using the PEDD approach. A recent study [ 51 ] investigated inherent noise/accuracy in the PEDD approach and identified temporal effects that may allow for analysis and filtering of EM interferences, thus allowing for a deeper comparison of both approaches in the presence of noise.…”

Section: Discussionmentioning

confidence: 99%

Advances in Optical Based Turbidity Sensing Using LED Photometry (PEDD)

Fay

Nattestad

2021

Self Cite

Turbidity is one of the primary metrics to determine water quality in terms of health and environmental concerns, however analysis typically takes place in centralized facilities, with samples periodically collected and transported there. Large scale autonomous deployments (WSNs) are impeded by both initial and per measurement costs. In this study we employ a Paired Emitter-Detector Diode (PEDD) technique to quantitatively measure turbidity using analytical grade calibration standards. Our PEDD approach compares favorably against more conventional photodiode-LED arrangements in terms of spectral sensitivity, cost, power use, sensitivity, limit of detection, and physical arrangement as per the ISO 7027 turbidity sensing standard. The findings show that the PEDD technique was superior in all aforementioned aspects. It is therefore more ideal for low-cost, low-power, IoT deployed sensors. The significance of these findings can lead to environmental deployments that greatly lower the device and per-measurement costs.

“…Additional advances can involve the introduction of the sensory targets. Examples include the development of cost-effective O 2 [57] and/or CO 2 [58] sensors based on LED detection technology [59][60][61]. In addition to cost-effectiveness, LED photometry via the PEDD technique offers improvements in sensitivities and resolution [62].…”

Section: Intelligence Integration and Autonomous Managementmentioning

confidence: 99%

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

Fay,

Healy,

Diamond

2023

Self Cite

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.