Previous Issue
Volume 13, December
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.9
3.3
Journals
JSAN
Volume 14
Issue 1
share announcement

J. Sens. Actuator Netw., Volume 14, Issue 1 (February 2025) – 15 articles

Cover Story (view full-size image): While wireless solutions usually dominate body sensor networks, wired methods excel where dense sensor/actuator deployments, low latency, and high reliability are needed. Despite decades of wired communication advancements, wearable applications have lagged behind, burdened by complex wiring and communication overhead. We address this gap by introducing a novel serial protocol with group addressing that cuts overhead by up to 50%, as well as demonstrating its use in an interactive jacket prototype over a semiduplex UART. Using only a three-wire bus for power and communication, the jacket supports nine sensors/actuators, achieving a 2.27 ms feedback delay and a 435.4 Hz frame rate, matching top-performing multi-node wearables while maintaining flexible, efficient wiring. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
38 pages, 13939 KiB  
Article
Online High-Definition Map Construction for Autonomous Vehicles: A Comprehensive Survey
by Hongyu Lyu, Julie Stephany Berrio Perez, Yaoqi Huang, Kunming Li, Mao Shan and Stewart Worrall
J. Sens. Actuator Netw. 2025, 14(1), 15; https://doi.org/10.3390/jsan14010015 - 2 Feb 2025
Viewed by 288
Abstract
High-definition (HD) maps aim to provide detailed road information with centimeter-level accuracy, essential for enabling precise navigation and safe operation of autonomous vehicles (AVs). Traditional offline construction methods involve several complex steps, such as data collection, point cloud generation, and feature extraction, but [...] Read more.
High-definition (HD) maps aim to provide detailed road information with centimeter-level accuracy, essential for enabling precise navigation and safe operation of autonomous vehicles (AVs). Traditional offline construction methods involve several complex steps, such as data collection, point cloud generation, and feature extraction, but these methods are resource-intensive and struggle to keep pace with the rapidly changing road environments. In contrast, online HD map construction leverages onboard sensor data to dynamically generate local HD maps, offering a bird’s-eye view (BEV) representation of the surrounding road environment. This approach has the potential to improve adaptability to spatial and temporal changes in road conditions while enhancing cost-efficiency by reducing the dependency on frequent map updates and expensive survey fleets. This survey provides a comprehensive analysis of online HD map construction, including the task background, high-level motivations, research methodology, key advancements, existing challenges, and future trends. We systematically review the latest advancements in three key sub-tasks: map segmentation, map element detection, and lane graph construction, aiming to bridge gaps in the current literature. We also discuss existing challenges and future trends, covering standardized map representation design, multitask learning, and multi-modality fusion, while offering suggestions for potential improvements. Full article
(This article belongs to the Special Issue Advances in Intelligent Transportation Systems (ITS))
19 pages, 3253 KiB  
Article
Optimization of Crop Yield in Precision Agriculture Using WSNs, Remote Sensing, and Atmospheric Simulation Models for Real-Time Environmental Monitoring
by Vincenzo Barrile, Clemente Maesano and Emanuela Genovese
J. Sens. Actuator Netw. 2025, 14(1), 14; https://doi.org/10.3390/jsan14010014 - 30 Jan 2025
Viewed by 462
Abstract
Due to the increasing demand for agricultural production and the depletion of natural resources, the rational and efficient use of resources in agriculture becomes essential. Thus, Agriculture 4.0 or precision agriculture (PA) was born, which leverages advanced technologies such as Geographic Information Systems [...] Read more.
Due to the increasing demand for agricultural production and the depletion of natural resources, the rational and efficient use of resources in agriculture becomes essential. Thus, Agriculture 4.0 or precision agriculture (PA) was born, which leverages advanced technologies such as Geographic Information Systems (GIS), Artificial Intelligence (AI), sensors and remote sensing techniques to optimize agricultural practices. This study focuses on an innovative approach integrating data from different sources, within a GIS platform, including data from an experimental atmospheric simulator and from a wireless sensor network, to identify the most suitable areas for future crops. In addition, we also calculate the optimal path of a drone for crop monitoring and for a farm machine for agricultural operations, improving efficiency and sustainability in relation to agricultural practices and applications. Expected and obtained results of the conducted study in a specific area of Reggio Calabria (Italy) include increased accuracy in agricultural planning, reduced resource and pesticide use, as well as increased yields and more sustainable management of natural resources. Full article
(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)
►▼ Show Figures

Figure 1

16 pages, 12215 KiB  
Article
An Intelligent Water Level Estimation System Considering Water Level Device Gauge Image Recognition and Wireless Sensor Networks
by Chihiro Yukawa, Tetsuya Oda, Takeharu Sato, Masaharu Hirota, Kengo Katayama and Leonard Barolli
J. Sens. Actuator Netw. 2025, 14(1), 13; https://doi.org/10.3390/jsan14010013 - 30 Jan 2025
Viewed by 369
Abstract
The control of water levels in various environments is very important for predicting flooding and mitigating flood damages. Generally, water level device gauges are used to measure water levels, but the structural setting of reservoirs presents significant challenges for the installation of water [...] Read more.
The control of water levels in various environments is very important for predicting flooding and mitigating flood damages. Generally, water level device gauges are used to measure water levels, but the structural setting of reservoirs presents significant challenges for the installation of water level device gauges. Therefore, the solution to this problem is to apply image recognition methods using water level device gauges. In this paper, we present an intelligent water level estimation system considering water level device gauge image recognition and a Wireless Sensor Network (WSN). We carried out experiments in a water reservoir to evaluate the proposed system. From the experimental results, we found that the proposed system can estimate the water level via the object recognition of numbers and symbols on the water level device gauge. Full article
(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)
13 pages, 828 KiB  
Article
Low-Complexity Ultrasonic Flowmeter Signal Processor Using Peak Detector-Based Envelope Detection
by Myeong-Geon Yu and Dong-Sun Kim
J. Sens. Actuator Netw. 2025, 14(1), 12; https://doi.org/10.3390/jsan14010012 - 30 Jan 2025
Viewed by 326
Abstract
Ultrasonic flowmeters are essential sensor devices widely used in remote metering systems, smart grids, and monitoring systems. In these environments, a low-power design is critical to maximize energy efficiency. Real-time data collection and remote consumption monitoring through remote metering significantly enhance network flexibility [...] Read more.
Ultrasonic flowmeters are essential sensor devices widely used in remote metering systems, smart grids, and monitoring systems. In these environments, a low-power design is critical to maximize energy efficiency. Real-time data collection and remote consumption monitoring through remote metering significantly enhance network flexibility and efficiency. This paper proposes a low-complexity structure that ensures an accurate time-of-flight (ToF) estimation within an acceptable error range while reducing computational complexity. The proposed system utilizes Hilbert envelope detection and a differentiator-based parallel peak detector. It transmits and collects data through ultrasonic transmitter and receiver transducers and is designed for seamless integration as a node into wireless sensor networks (WSNs). The system can be involved in various IoT and industrial applications through high energy efficiency and real-time data transmission capabilities. The proposed structure was validated using the MATLAB software, with an LPG gas flowmeter as the medium. The results demonstrated a mean relative deviation of 5.07% across a flow velocity range of 0.1–1.7 m/s while reducing hardware complexity by 78.9% compared to the conventional FFT-based cross-correlation methods. This study presents a novel design integrating energy-efficient ultrasonic flowmeters into remote metering systems, smart grids, and industrial monitoring applications. Full article
(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)
23 pages, 2095 KiB  
Article
Federated Learning for Privacy-Friendly Health Apps: A Case Study on Ovulation Tracking
by Nikolaos Pavlidis, Andreas Sendros, Theodoros Tsiolakis, Periklis Kostamis, Christos Karasoulas, Eleni Briola, Christos Chrysanthos Nikolaidis, Vasilis Perifanis, George Drosatos, Eleftheria Katsiri, Despoina Elisavet Filippidou, Anastasios Manos and Pavlos S. Efraimidis
J. Sens. Actuator Netw. 2025, 14(1), 11; https://doi.org/10.3390/jsan14010011 - 29 Jan 2025
Viewed by 344
Abstract
In an era of increasing reliance on digital health solutions, safeguarding user privacy has emerged as a paramount concern. Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement. This paper presents the architecture of FLORA, [...] Read more.
In an era of increasing reliance on digital health solutions, safeguarding user privacy has emerged as a paramount concern. Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement. This paper presents the architecture of FLORA, a privacy-first ovulation-tracking application that leverages federated learning (FL), privacy-enhancing technologies (PETs), and blockchain to protect user data while delivering accurate and personalized health insights. Unlike conventional centralized systems, FLORA ensures that sensitive information remains on users’ devices, with predictive algorithms powered by local computations. Blockchain technology provides immutable consent tracking and model update transparency, further improving user trust. In addition, FLORA’s design incentivizes participation through a token-based reward system, fostering collaborative data contributions. This work illustrates how the integration of cutting-edge technologies creates a secure, scalable, and user-centric health application, setting a new standard for privacy-preserving digital health platforms. Full article
(This article belongs to the Special Issue Federated Learning: Applications and Future Directions)
22 pages, 6801 KiB  
Article
A Novel Approach to Road Safety: Detecting Illegal Overtaking Using Smartphone Cameras and Deep Learning for Vehicle Auditing
by Karem Daiane Marcomini, Vitória de Carvalho Brito, Gregori da Cruz Balestra, Vitor Tosetto, Luiz Carlos Duarte and Antonio Roberto Donadon
J. Sens. Actuator Netw. 2025, 14(1), 10; https://doi.org/10.3390/jsan14010010 - 26 Jan 2025
Viewed by 461
Abstract
Overtaking relies heavily on the driver’s attention and cognitive state, and illegal overtaking can lead to accidents, severe injuries, or fatalities. To enhance highway safety, we propose a method for accurately detecting illegal overtaking on continuous road lanes. We used dashboard-mounted smartphone cameras [...] Read more.
Overtaking relies heavily on the driver’s attention and cognitive state, and illegal overtaking can lead to accidents, severe injuries, or fatalities. To enhance highway safety, we propose a method for accurately detecting illegal overtaking on continuous road lanes. We used dashboard-mounted smartphone cameras and geolocation data to filter the analysis areas. We used the state-of-the-art deep learning model You Only Look Once version 8 (YOLOv8) to detect yellow road lanes. When these lanes suggest potential illegal overtaking, we apply the YOLO for Panoptic driving Perception version 2 (YOLOPv2) model, followed by post-processing. We confirm overtaking events by checking for overlaps between detections from both models. We store confirmed instances and evaluate the information temporally rather than just from individual frames. We then analyze the entire video to identify violations and extract the moments of occurrence. We tested the algorithm on real-world traffic data under various weather and lighting conditions. Our method demonstrates reliability and consistency in identifying illegal overtaking. We achieved 16 TP and only 1 FP over 56 videos totaling 41 h, 9 min, and 24 s, with precision, recall, and F1-score values of 1.000, 0.941, and 0.970, respectively. Consequently, our innovative and practical solution, utilizing simple cameras and advanced computer vision models, can significantly enhance highway safety and support vehicle auditing systems. Full article
(This article belongs to the Special Issue Advances in Intelligent Transportation Systems (ITS))
►▼ Show Figures

Figure 1

25 pages, 405 KiB  
Review
Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications
by Elias Dritsas and Maria Trigka
J. Sens. Actuator Netw. 2025, 14(1), 9; https://doi.org/10.3390/jsan14010009 - 22 Jan 2025
Viewed by 680
Abstract
Federated Learning (FL) has emerged as a pivotal approach for decentralized Machine Learning (ML), addressing the unique demands of the Internet of Things (IoT) environments where data privacy, bandwidth constraints, and device heterogeneity are paramount. This survey provides a comprehensive overview of FL, [...] Read more.
Federated Learning (FL) has emerged as a pivotal approach for decentralized Machine Learning (ML), addressing the unique demands of the Internet of Things (IoT) environments where data privacy, bandwidth constraints, and device heterogeneity are paramount. This survey provides a comprehensive overview of FL, focusing on its integration with the IoT. We delve into the motivations behind adopting FL for IoT, the underlying techniques that facilitate this integration, the unique challenges posed by IoT environments, and the diverse range of applications where FL is making an impact. Finally, this submission also outlines future research directions and open issues, aiming to provide a detailed roadmap for advancing FL in IoT settings. Full article
(This article belongs to the Special Issue Federated Learning: Applications and Future Directions)
►▼ Show Figures

Figure 1

33 pages, 4796 KiB  
Article
Edge Computing-Aided Dynamic Wireless Charging and Trip Planning of UAVs
by Palwasha W. Shaikh and Hussein T. Mouftah
J. Sens. Actuator Netw. 2025, 14(1), 8; https://doi.org/10.3390/jsan14010008 - 16 Jan 2025
Viewed by 492
Abstract
In today’s era of rapid technological advancement, unmanned aerial vehicles (UAVs) are transforming sectors such as remote delivery, surveillance, and disaster response. However, challenges related to energy consumption and operational efficiency continue to hinder their broader adoption. To address these issues, this study [...] Read more.
In today’s era of rapid technological advancement, unmanned aerial vehicles (UAVs) are transforming sectors such as remote delivery, surveillance, and disaster response. However, challenges related to energy consumption and operational efficiency continue to hinder their broader adoption. To address these issues, this study proposes an integrated system design combining dynamic wireless charging (DWC), intelligent trip planning, and intelligent edge computing (IEC). The proposed system leverages IEC for local data processing to reduce latency and optimize energy management, 6G networks for real-time vehicle-to-infrastructure (V2I) communication, and DWC to enable efficient, on-the-go energy replenishment. Additionally, a dynamic arrival management algorithm is introduced to minimize UAV wait times to enhance operational efficiency. Simulations of this system demonstrated significant improvements: larger UAVs achieved an average charging efficiency of 91.2%, while smaller UAVs achieved 92.75%, with dynamic arrival management reducing wait times by an average of 1.5 min for smaller UAVs and 5.0 min for larger UAVs. These findings underscore the system’s effectiveness in optimizing UAV operations and charging efficiency. This integrated approach offers a scalable framework to enhance UAV capabilities and sets a benchmark for future advancements in operational efficiency and charging technology for urban and environmental applications. Full article
(This article belongs to the Special Issue Applications of Wireless Sensor Networks: Innovations and Future Trends)
►▼ Show Figures

Graphical abstract

59 pages, 2891 KiB  
Review
Event-Based Visual Simultaneous Localization and Mapping (EVSLAM) Techniques: State of the Art and Future Directions
by Mohsen Shahraki, Ahmed Elamin and Ahmed El-Rabbany
J. Sens. Actuator Netw. 2025, 14(1), 7; https://doi.org/10.3390/jsan14010007 - 14 Jan 2025
Viewed by 557
Abstract
Recent advances in event-based cameras have led to significant developments in robotics, particularly in visual simultaneous localization and mapping (VSLAM) applications. This technique enables real-time camera motion estimation and simultaneous environment mapping using visual sensors on mobile platforms. Event cameras offer several distinct [...] Read more.
Recent advances in event-based cameras have led to significant developments in robotics, particularly in visual simultaneous localization and mapping (VSLAM) applications. This technique enables real-time camera motion estimation and simultaneous environment mapping using visual sensors on mobile platforms. Event cameras offer several distinct advantages over frame-based cameras, including a high dynamic range, high temporal resolution, low power consumption, and low latency. These attributes make event cameras highly suitable for addressing performance issues in challenging scenarios such as high-speed motion and environments with high-range illumination. This review paper delves into event-based VSLAM (EVSLAM) algorithms, leveraging the advantages inherent in event streams for localization and mapping endeavors. The exposition commences by explaining the operational principles of event cameras, providing insights into the diverse event representations applied in event data preprocessing. A crucial facet of this survey is the systematic categorization of EVSLAM research into three key parts: event preprocessing, event tracking, and sensor fusion algorithms in EVSLAM. Each category undergoes meticulous examination, offering practical insights and guidance for comprehending each approach. Moreover, we thoroughly assess state-of-the-art (SOTA) methods, emphasizing conducting the evaluation on a specific dataset for enhanced comparability. This evaluation sheds light on current challenges and outlines promising avenues for future research, emphasizing the persisting obstacles and potential advancements in this dynamically evolving domain. Full article
(This article belongs to the Section Actuators, Sensors and Devices)
►▼ Show Figures

Figure 1

47 pages, 14403 KiB  
Review
Chemical Detection Using Mobile Platforms and AI-Based Data Processing Technologies
by Daegwon Noh and Eunsoon Oh
J. Sens. Actuator Netw. 2025, 14(1), 6; https://doi.org/10.3390/jsan14010006 - 13 Jan 2025
Viewed by 598
Abstract
The development of reliable gas sensors is very important in many fields such as safety, environment, and agriculture, and is especially essential for industrial waste and air pollution monitoring. As the performance of mobile platforms equipped with sensors such as smartphones and drones [...] Read more.
The development of reliable gas sensors is very important in many fields such as safety, environment, and agriculture, and is especially essential for industrial waste and air pollution monitoring. As the performance of mobile platforms equipped with sensors such as smartphones and drones and the technologies supporting them (wireless communication, battery performance, data processing technology, etc.) are spreading and improving, a lot of efforts are being made to perform these tasks by using portable systems such as smartphones or installing them on unmanned wireless platforms such as drones. For example, research is continuously being conducted on chemical sensors for field monitoring using smartphones and rapid monitoring of air pollution using unmanned aerial vehicles (UAVs). In this paper, we review the measurement results of various chemical sensors available on mobile platforms including drones and smartphones, and the analysis of detection results using machine learning. This topic covers a wide range of specialized fields such as materials engineering, aerospace engineering, physics, chemistry, environmental engineering, electrical engineering, and machine learning, and it is difficult for experts in one field to grasp the entire content. Therefore, we have explained various concepts with relatively simple pictures so that experts in various fields can comprehensively understand the overall topics. Full article
(This article belongs to the Section Big Data, Computing and Artificial Intelligence)
►▼ Show Figures

Figure 1

22 pages, 12995 KiB  
Article
Sensor-Based Detection of Characteristics of Rubber Springs
by Leopold Hrabovský, Jan Blata, Ladislav Kovář, Michal Kolesár and Jaromír Štěpáník
J. Sens. Actuator Netw. 2025, 14(1), 5; https://doi.org/10.3390/jsan14010005 - 9 Jan 2025
Viewed by 441
Abstract
Knowledge of experimentally obtained values of elastic deformations of rubber springs induced by applied compressive forces of known magnitudes is essential for the selection of rubber springs with optimal properties, which are used to dampen vibrations transmitted to the supporting parts of vibrating [...] Read more.
Knowledge of experimentally obtained values of elastic deformations of rubber springs induced by applied compressive forces of known magnitudes is essential for the selection of rubber springs with optimal properties, which are used to dampen vibrations transmitted to the supporting parts of vibrating machines. This paper deals with the laboratory measurement of the characteristics of rubber springs using two types of sensors which sense the instantaneous value of the compressive force acting on the compressed spring. When using a strain tensometric force sensor, the magnitude of the measured pressure forces was evaluated by the DeweSoft DS-NET system, which was connected to an ethernet LAN, so the measured data could be processed, analysed and stored by any computer on the network. The characteristics of eight types of rubber springs were measured in two ways on laboratory equipment, and the spring stiffnesses were calculated from the measured data. Experiments have shown that the actual stiffnesses of rubber springs are lower compared to the values stated by the manufacturer, in the least favourable case, by 33.6%. It has been shown by measurements that at the beginning of the loading of the rubber spring, its compression is gradual, and the stiffness increases slowly, which is defined as the progressivity of the spring. Full article
(This article belongs to the Section Actuators, Sensors and Devices)
►▼ Show Figures

Figure 1

20 pages, 5332 KiB  
Article
An Efficient Communication Protocol for Real-Time Body Sensor Data Acquisition and Feedback in Interactive Wearable Systems
by Armands Ancans, Modris Greitans and Sandis Kagis
J. Sens. Actuator Netw. 2025, 14(1), 4; https://doi.org/10.3390/jsan14010004 - 30 Dec 2024
Viewed by 663
Abstract
We introduce a novel wired communication approach for interactive wearable systems, employing a single signal wire and innovative group addressing protocol to reduce overhead. While wireless solutions dominate body sensor networks, wired approaches offer advantages for interactive applications that require low latency, high [...] Read more.
We introduce a novel wired communication approach for interactive wearable systems, employing a single signal wire and innovative group addressing protocol to reduce overhead. While wireless solutions dominate body sensor networks, wired approaches offer advantages for interactive applications that require low latency, high reliability, and communication with high-density nodes; yet they have been less explored in the context of wearable systems. Many commercial products use wired connections without disclosing technical details, limiting broader adoption. To address this gap, we present and test a new group addressing protocol implemented using Universal Asynchronous Receiver–Transmitter (UART) hardware, disclosing frame diagrams and node architectures. We developed a prototype interactive jacket with nine sensor/actuator nodes connected via three wires for power supply and data transmission to a wireless gateway. Mathematical analysis showed an overhead reduction of approximately 50% compared to traditional individual addressing. Our solution is the most wire-efficient among wired interactive wearable systems reviewed in the literature, using only one signal wire; other methods require at least two wires and often have overlapping topologies. Performance experimental evaluation revealed a total feedback delay of 2.27 ms and a maximum data frame rate of 435.4 Hz, comparable to the best-performing products and leaving room for twice the performance calculated theoretically. These results indicate that the proposed approach is suitable for interactive wearable systems, both for real-time applications and high-resolution data acquisition. Full article
(This article belongs to the Section Communications and Networking)
►▼ Show Figures

Figure 1

22 pages, 11697 KiB  
Article
Generalizable Solar Irradiance Prediction for Battery Operation Optimization in IoT-Based Microgrid Environments
by Ray Colucci and Imad Mahgoub
J. Sens. Actuator Netw. 2025, 14(1), 3; https://doi.org/10.3390/jsan14010003 - 27 Dec 2024
Viewed by 655
Abstract
The reliance on fossil fuels as a primary global energy source has significantly impacted the environment, contributing to pollution and climate change. A shift towards renewable energy sources, particularly solar power, is underway, though these sources face challenges due to their inherent intermittency. [...] Read more.
The reliance on fossil fuels as a primary global energy source has significantly impacted the environment, contributing to pollution and climate change. A shift towards renewable energy sources, particularly solar power, is underway, though these sources face challenges due to their inherent intermittency. Battery energy storage systems (BESS) play a crucial role in mitigating this intermittency, ensuring a reliable power supply when solar generation is insufficient. The objective of this paper is to accurately predict the solar irradiance for battery operation optimization in microgrids. Using satellite data from weather sensors, we trained machine learning models to enhance solar irradiance predictions. We evaluated five popular machine learning algorithms and applied ensemble methods, achieving a substantial improvement in predictive accuracy. Our model outperforms previous works using the same dataset and has been validated to generalize across diverse geographical locations in Florida. This work demonstrates the potential of AI-assisted data-driven approaches to support sustainable energy management in solar-powered IoT-based microgrids. Full article
(This article belongs to the Special Issue AI-Assisted Machine-Environment Interaction)
►▼ Show Figures

Figure 1

26 pages, 6009 KiB  
Article
Enhancing Campus Environment: Real-Time Air Quality Monitoring Through IoT and Web Technologies
by Alfiandi Aulia Rahmadani, Yan Watequlis Syaifudin, Budhy Setiawan, Yohanes Yohanie Fridelin Panduman and Nobuo Funabiki
J. Sens. Actuator Netw. 2025, 14(1), 2; https://doi.org/10.3390/jsan14010002 - 25 Dec 2024
Viewed by 724
Abstract
Nowadays, enhancing campus environments through mitigations of air pollutions is an essential endeavor to support academic achievements, health, and safety of students and staffs in higher educational institutes. In laboratories, pollutants from welding, auto repairs, or chemical experiments can drastically degrade the air [...] Read more.
Nowadays, enhancing campus environments through mitigations of air pollutions is an essential endeavor to support academic achievements, health, and safety of students and staffs in higher educational institutes. In laboratories, pollutants from welding, auto repairs, or chemical experiments can drastically degrade the air quality in the campus, endangering the respiratory and cognitive health of students and staffs. Besides, in universities in Indonesia, automobile emissions of harmful substances such as carbon monoxide (CO), nitrogen dioxide (NO2), and hydrocarbon (HC) have been a serious problem for a long time. Almost everybody is using a motorbike or a car every day in daily life, while the number of students is continuously increasing. However, people in many campuses including managements do not be aware these problems, since air quality is not monitored. In this paper, we present a real-time air quality monitoring system utilizing Internet of Things (IoT) integrated sensors capable of detecting pollutants and measuring environmental conditions to visualize them. By transmitting data to the SEMAR IoT application server platform via an ESP32 microcontroller, this system provides instant alerts through a web application and Telegram notifications when pollutant levels exceed safe thresholds. For evaluations of the proposed system, we adopted three sensors to measure the levels of CO, NO2, and HC and conducted experiments in three sites, namely, Mechatronics Laboratory, Power and Emission Laboratory, and Parking Lot, at the State Polytechnic of Malang, Indonesia. Then, the results reveal Good, Unhealthy, and Dangerous for them, respectively, among the five categories defined by the Indonesian government. The system highlighted its ability to monitor air quality fluctuations, trigger warnings of hazardous conditions, and inform the campus community. The correlation of the sensor levels can identify the relationship of each pollutant, which provides insight into the characteristics of pollutants in a particular scenario. Full article
(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)
►▼ Show Figures

Figure 1

20 pages, 5477 KiB  
Article
Development of Virtual Water Flow Sensor Using Valve Performance Curve
by Taeyang Kim, Hyojun Kim, Jinhyun Lee and Younghum Cho
J. Sens. Actuator Netw. 2025, 14(1), 1; https://doi.org/10.3390/jsan14010001 - 24 Dec 2024
Viewed by 451
Abstract
This research focuses on addressing the limitations of conventional physical sensors and developing a virtual water flow rate prediction technology. With HVAC systems being increasingly adopted, research on optimizing control settings based on load variations is critical. Existing systems often operate based on [...] Read more.
This research focuses on addressing the limitations of conventional physical sensors and developing a virtual water flow rate prediction technology. With HVAC systems being increasingly adopted, research on optimizing control settings based on load variations is critical. Existing systems often operate based on peak load conditions, leading to energy overconsumption in partial load scenarios. Physical sensors used for water flow measurement face challenges such as installation difficulties in constrained spaces and increased costs in large buildings. Virtual water flow rate prediction technology offers a cost-effective solution by leveraging in situ measurement data instead of extensive physical sensors. To achieve this, a test bed with a pump, valve, and heat pump was used, controlled via a BAS. Water flow rate was measured using an ultrasonic flow meter, and differential pressure was recorded using pressure gauges. Equations were developed to replace differential pressure values with valve opening rates and pump speeds by deriving performance curves and differential pressure ratio equations. Measurement uncertainty was calculated to assess the reliability of the experimental setup. Various test numbers were created to evaluate the virtual water flow rate model under controlled conditions. The results showed that relative errors ranged from 0.32% to 10.54%, with RMSE, MBE, and CvRMSE meeting all threshold criteria. The virtual water flow rate model demonstrated strong predictive accuracy and reliability, supported by an R2 value close to 1. This research confirms the effectiveness of the proposed model for reducing the dependence on physical sensors while enabling accurate water flow rate predictions in HVAC systems. Full article
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-15
Previous Issue
Back to TopTop