A Resilient LoRa-Based Solution to Support Pervasive Sensing DOI Open Access
Pietro Manzoni, Salah Eddine Merzougui, Claudio E. Palazzi

et al.

Electronics, Journal Year: 2023, Volume and Issue: 12(13), P. 2952 - 2952

Published: July 5, 2023

Today, billions of small devices that can sense things are connected, creating the Internet Things (IoT). This major technological step has led to ideas like smart cities, factories, and countries. One important use this technology is pervasive sensing, which could benefit from a network covers wide area but does not much power. paper looks closely at advantages disadvantages using LoRa—a reach long distances with limited energy use—in situations this. To aim, we have created holistic solution manage considered enabling synchronization, routing, reliability. In particular, even developed an adaptive spreading factor mechanism, simple effective in allowing cope better when connection very good.

Language: Английский

Real-time IoT-powered AI system for monitoring and forecasting of air pollution in industrial environment DOI Creative Commons
Montaser N.A. Ramadan, Mohammed A. H. Ali,

Shin Yee Khoo

et al.

Ecotoxicology and Environmental Safety, Journal Year: 2024, Volume and Issue: 283, P. 116856 - 116856

Published: Aug. 15, 2024

Air pollution in industrial environments, particularly the chrome plating process, poses significant health risks to workers due high concentrations of hazardous pollutants. Exposure substances like hexavalent chromium, volatile organic compounds (VOCs), and particulate matter can lead severe issues, including respiratory problems lung cancer. Continuous monitoring timely intervention are crucial mitigate these risks. Traditional air quality methods often lack real-time data analysis predictive capabilities, limiting their effectiveness addressing hazards proactively. This paper introduces a forecasting system specifically designed for industry. The system, supported by Internet Things (IoT) sensors AI approaches, detects wide range pollutants, NH

Language: Английский

Citations

19
AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings DOI Creative Commons

Dalia Mohammed Talat Ebrahim Ali,

Violeta Motuzienė, Rasa Džiugaitė-Tumėnienė

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(17), P. 4277 - 4277

Published: Aug. 27, 2024

Despite the tightening of energy performance standards for buildings in various countries and increased use efficient renewable technologies, it is clear that sector needs to change more rapidly meet Net Zero Emissions (NZE) scenario by 2050. One problems have been analyzed intensively recent years operation much than they were designed to. This problem, known as gap, found many often attributed poor management building systems. The application Artificial Intelligence (AI) Building Energy Management Systems (BEMS) has untapped potential address this problem lead sustainable buildings. paper reviews different AI-based models proposed applications with intention reduce consumption. It compares evaluated reviewed papers presenting accuracy error rates model identifies where greatest savings could be achieved, what extent. review showed offices (up 37%) when employ AI HVAC control optimization. In residential educational buildings, lower intelligence existing BEMS results smaller 23% 21%, respectively).

Language: Английский

Citations

11
Effectiveness of a negative ion generator “Instashield” for indoor air disinfection: evidence from tertiary care hospital and GLP laboratory settings DOI
Neema Kumari, Vikas Sahu,

Kavitha Chintala

et al.

Bulletin of Atmospheric Science and Technology, Journal Year: 2025, Volume and Issue: 6(1)

Published: Jan. 29, 2025

Language: Английский

Citations

0
Prisma-Based Review Of Mis Solutions For Enhanced Disaster Response And Resource Allocation DOI

Emdadul Haque,

Zayadul Hasan

SSRN Electronic Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
A Regional Multi-Agent Air Monitoring Platform DOI Creative Commons
Stanimir Stoyanov, Emil Doychev, Asya Stoyanova-Doycheva

et al.

Future Internet, Journal Year: 2025, Volume and Issue: 17(3), P. 112 - 112

Published: March 3, 2025

Plovdiv faces significant air pollution challenges due to geographic, climatic, and industrial factors, making accurate quality assessment critical. This study presents a hybrid multi-agent platform that integrates symbolic sub-symbolic artificial intelligence improve the reliability of monitoring. The features BDI agent, developed using JaCaMo, for processing real-time sensor measurements ReAct implemented with LangChain, incorporate external data sources perform advanced analytics. By combining these AI approaches, enhances integration, detects anomalies, resolves discrepancies between conflicting reports. Furthermore, its scalable adaptable architecture lays foundation future advancements in environmental research represents first stage developing an AI-powered system supports more objective data-driven decision-making management Plovdiv.

Language: Английский

Citations

0
Multi-Sensor Platform in Precision Livestock Farming for Air Quality Measurement Based on Open-Source Tools DOI Creative Commons
Victor Danev, Tatiana Atanasova, Kristina Dineva

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(18), P. 8113 - 8113

Published: Sept. 10, 2024

Monitoring air quality in livestock farming facilities is crucial for ensuring the health and well-being of both animals workers. As can contribute to emission various gaseous particulate pollutants, there a pressing need advanced monitoring systems manage mitigate these emissions effectively. This study introduces multi-sensor system designed specifically environments. Utilizing open-source tools low-cost sensors, measure multiple parameters simultaneously. The architecture based on SOLID principles ensure robustness, scalability, ease maintenance. Understanding trend evolution from single-parameter measurements more holistic approach through integration platform proposed this work. shift towards driven by recognition that comprehensive understanding requires consideration diverse pollutants environmental factors. aim construct with use sensors as tool Precision Livestock Farming (PLF). Analysis data collected device reveals some insights into conditions monitored barn. Time-series correlation analyses revealed significant interactions between key parameters, such strong positive correlations ammonia hydrogen sulfide, total volatile organic compounds carbon dioxide. These relationships highlight critical impact odorants quality, emphasizing effective barn controls

Language: Английский

Citations

2
Prototype of Monitoring Transportation Pollution Spikes through the Internet of Things Edge Networks DOI Creative Commons
Eric Nizeyimana, Damien Hanyurwimfura, Junseok Hwang

et al.

Sensors, Journal Year: 2023, Volume and Issue: 23(21), P. 8941 - 8941

Published: Nov. 3, 2023

Air pollution is a critical problem in densely populated urban areas, with traffic significantly contributing. To mitigate the adverse effects of air on public health and environment, there growing need for real-time monitoring detection spikes transportation. This paper presents novel approach to using Internet Things (IoT) edge networks peaks transportation, specifically designed innovative city applications. The proposed system uses IoT sensors buses, cabs, private cars. These are equipped quality capabilities, including measurement pollutants such as particulate matter (PM2.5 PM10), nitrogen dioxide (NO2), ozone (O3), sulfur (SO2), carbon (CO2). continuously collect data transmit them devices within transportation infrastructure. collected by these analyzed, alerts generated when levels exceed predefined thresholds. By deploying this networks, authorities can promptly respond spikes, improving quality, health, environmental sustainability. details sensor technology, analysis methods, practical implementation system, shedding light its potential addressing pressing issue transportation-related pollution. network spike offers significant advantages, low-latency processing, scalability, cost-effectiveness. leveraging power computing technologies, smart cities proactively monitor manage pollution, leading healthier more sustainable environments.

Language: Английский

Citations

4
Study on Sensor Fault-Tolerant Control for Central Air-Conditioning Systems Using Bayesian Inference with Data Increments DOI Creative Commons
Guannan Li, Chongchong Wang, Lamei Liu

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(4), P. 1150 - 1150

Published: Feb. 9, 2024

A lack of available information on heating, ventilation, and air-conditioning (HVAC) systems can affect the performance data-driven fault-tolerant control (FTC) models. This study proposed an in situ selective incremental calibration (ISIC) strategy. Faults were introduced into indoor air (Ttz1) thermostat supply temperature (Tsa) chilled water (Tchws) sensors a central system. The changes system after FTC evaluated. Then, we considered effects data quality, volume, variable number results. For Ttz1 Tsa sensor, energy consumption was reduced by 2.98% 3.72% with ISIC, respectively, predicted percentage dissatisfaction 0.67% 0.63%, respectively. Better results obtained using ISIC when had low noise, 7-day or sufficient variables Tchws 14-day limited variables.

Language: Английский

Citations

1
Blockchain and IoT integration for secure short-term and long-term air quality monitoring system using optimized neural network DOI

Balasubramanian Chinnappan,

K.M. Hakim,

Neelam Sanjeev Kumar

et al.

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(27), P. 39372 - 39387

Published: May 31, 2024

Language: Английский

Citations

1
A systematic review of multi-output prediction model for indoor environment and heating, ventilation, and air conditioning energy consumption in buildings DOI
Kaiyun Jiang, Tianyu Shi, Haowei Yu

et al.

Indoor and Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: June 13, 2024

Heating, ventilation and air conditioning (HVAC) systems could significantly impact indoor environmental quality, particularly in terms of thermal comfort quality. Achieving a high-quality environment poses challenges to the energy consumption HVAC systems. Thus, balancing comfort, quality (IAQ) becomes challenging task. Currently, prediction methods are considered effective solutions address this issue. However, published literature usually concentrates on single aspects like or consumption, with multi-aspect being rare. The present work reviews research spanning last decade that employs machine learning for predicting environments through separate multi-output predictive models. Separate models focus systems’ environment, while consider interplay various outputs. This article gives thorough insight into models’ workflow, detailing data collection, feature selection model optimization each goal. A systematic assessment collection diverse targets, algorithms validation approaches different is presented. review highlights complexities management, development validation, enriching knowledge base optimization.

Language: Английский

Citations

1