Weak Constraint Gaussian Processes for optimal sensor placement

Dur, Tolga Hasan; Arcucci, Rossella; Mottet, Laetitia; Solana, Miguel Molina; Pain, Christopher C.; Guo, Yike

doi:10.1016/j.jocs.2020.101110

Cited by 7 publications

(3 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many authors have investigated the optimal placement of sensors. For example, the studies on the Gaussian Process model for optimal sensor placement by Dur et al [48], Krause et al [49], Longi et al [50], and [51].…”

Section: Optimal Iot Setup Placement Studiesmentioning

confidence: 99%

The State-of-the-Art in Air Pollution Monitoring and Forecasting Systems Using IoT, Big Data, and Machine Learning

Gangwar

Singh

Mishra

et al. 2023

Wireless Pers Commun

View full text Add to dashboard Cite

The quality of air is closely linked with the life quality of humans, plantations, and wildlife. It needs to be monitored and preserved continuously. Transportations, industries, construction sites, generators, fireworks, and waste burning have a major percentage in degrading the air quality. These sources are required to be used in a safe and controlled manner. Using traditional laboratory analysis or installing bulk and expensive models every few miles is no longer efficient. Smart devices are needed for collecting and analyzing air data. The quality of air depends on various factors, including location, traffic, and time. Recent researches are using machine learning algorithms, big data technologies, and the Internet of Things to propose a stable and efficient model for the stated purpose. This review paper focuses on studying and compiling recent research in this field and emphasizes the Data sources, Monitoring, and Forecasting models. The main objective of this paper is to provide the astuteness of the researches happening to improve the various aspects of air polluting models. Further, it casts light on the various research issues and challenges also.

show abstract

Section: Optimal Iot Setup Placement Studiesmentioning

confidence: 99%

The State-of-the-Art in Air Pollution Monitoring and Forecasting Systems Using IoT, Big Data, and Machine Learning

Gangwar

Singh

Mishra

et al. 2023

Wireless Pers Commun

View full text Add to dashboard Cite

show abstract

“…Their proposal was tested on real and hard instances provided by the company. In [ 33 ], Dur et al present a weak constraint Gaussian process model to integrate noisy inputs into the classical Gaussian process predictive distribution. To implement a high-performance computing environment, parallelism is explored by defining a parallel weak constraint Gaussian process model which is based on domain decomposition.…”

Section: Overview Of the Virtual Special Issuementioning

confidence: 99%

Computational Science in the Interconnected World: Selected papers from 2019 International Conference on Computational Science

Cardoso

Rodrigues

Monteiro

et al. 2020

Journal of Computational Science

View full text Add to dashboard Cite

“…According to the analysis of temperature spatial distribution based on a computational fluid dynamics (CFD) simulation, the temperature sensors were suggested to be installed at the locations with the lowest gradient of temperature and airflow velocity [11,12]. With the objective of maximizing the monitoring coverage area, temperature sensors and air pollutant sensors were optimized for deployment, respectively, which helped the full exploitation of the monitoring capabilities of the sensor unit and reduced sensor quantity [13][14][15][16]. With the rapid development of machine learning and artificial intelligence, the configurations of temperature sensors and CO 2 sensors were, respectively, optimized in large stadiums and other buildings with the use of different algorithms [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Configuration Optimization of Temperature–Humidity Sensors Based on Weighted Hilbert–Schmidt Independence Criterion in Chinese Solar Greenhouses

Song,

Liu,

Liu

et al. 2024

Agriculture

View full text Add to dashboard Cite

For cost-sensitive Chinese solar greenhouses (CSGs) with an uneven spatial distribution in temperature and humidity, there is a lack of effective strategies for sensor configuration that can reduce sensor usage while monitoring the microclimate precisely. A configuration strategy for integrated temperature–humidity sensors (THSs) based on the improved weighted Hilbert–Schmidt independence criterion (HSIC) is proposed in this paper. The data independence of the THSs in different sites was analyzed based on the improved HSIC, and the selection priority of the THSs was ranked based on the weighted independence of temperature and humidity. Then, according to different cost constraints and monitoring requirements, suitable THSs could be selected sequentially and constitute the monitoring solution. Compared with the original monitoring solution containing twenty-two THSs, the optimized solution used only four THSs (S6, S9 and H6, H5) under strict cost constraints, with a maximum RMSE of the temperature and relative humidity of 0.6 °C and 2.30%, as well as a maximum information gain rate (IGR) of 9.47% and 10.0%. If higher monitoring precision is required, we can increase the THS usage with a greater budget. The optimized solution with six THSs (S6, S9, S8 and H6, H5, H2) could further reduce the maximum RMSE of the temperature and relative humidity to 0.33 °C and 1.10% and the IGR to 6.9% and 8.7%. This indicated that the proposed strategy could use much fewer THSs to achieve accurate and comprehensive monitoring, which would provide efficient and low-cost solutions for CSG microclimate monitoring.

show abstract

Weak Constraint Gaussian Processes for optimal sensor placement

Cited by 7 publications

References 19 publications

The State-of-the-Art in Air Pollution Monitoring and Forecasting Systems Using IoT, Big Data, and Machine Learning

The State-of-the-Art in Air Pollution Monitoring and Forecasting Systems Using IoT, Big Data, and Machine Learning

Computational Science in the Interconnected World: Selected papers from 2019 International Conference on Computational Science

Configuration Optimization of Temperature–Humidity Sensors Based on Weighted Hilbert–Schmidt Independence Criterion in Chinese Solar Greenhouses

Contact Info

Product

Resources

About