Article
Computer Science, Information Systems
Cheng-Chang Chiu, Teh-Lu Liao, Chiung-Hsing Chen, Shao-En Kao
Summary: Different fish species and growth stages have different feeding requirements. Excessive feeding increases costs and leads to water pollution. This article presents an improved fish feeder using the AIoT precision feeding management system, which utilizes a buoy and accelerometer to measure water surface fluctuations and adjust feeding time. This intelligent feeding system aims to reduce aquaculture costs.
Article
Engineering, Electrical & Electronic
Haohui Chen, Xinyuan Nan, Sibo Xia
Summary: A high-precision fusion strategy is proposed for temperature monitoring in aquaculture ponds, which includes preprocessing the temperature data using an improved unscented Kalman filter, fusing the data collected from sensors at the local fusion center using sequential analysis and fast inverse covariance intersection (ICI) algorithm, and fusing the temperature data from the middle layer at the global fusion center using an improved seagull algorithm to optimize the extreme learning machine (ELM) algorithm. The results demonstrate that the fusion strategy reduces external interference, improves the accuracy of global optimal temperature state estimation, and ensures the stability and accuracy of data fusion.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Wu-Chih Hu, Liang-Bi Chen, Bo-Kai Huang, Hong-Ming Lin
Summary: This article proposes an automatic fish feeding system based on deep learning computer vision technology to recognize the size of the water waves caused by fish eating feed and uses water quality sensors to assist in feeding decisions. Experimental results show that the system can achieve an accuracy of up to 93.2%.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Environmental
Jacquelyn Q. Q. Schmidt, Branko Kerkez
Summary: This study presents a machine learning-assisted methodology for detecting faulty environmental sensor data. By embedding sensor measurements into a dynamical feature space and training a binary classification algorithm, our proposed methodology achieved high accuracy and consistently outperformed existing techniques. The methodology is applied to three novel data sets produced by low-cost environmental sensors deployed across a large area in Michigan, USA.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Computer Science, Hardware & Architecture
Abuu B. Kihero, Haji M. Furqan, M. M. Sahin, Huseyin Arslan
Summary: Security is a critical requirement for future wireless networks, and physical layer security utilizes random wireless channel features to protect communication information and processes. Future wireless networks will offer more channel features for physical layer security to meet new use case demands.
IEEE WIRELESS COMMUNICATIONS
(2023)
Article
Environmental Sciences
Rubens Zenko Sakiyama, Emilio Soitsi Junior Zukeram, Linnyer Beatrys Ruiz, Cid Marcos Goncalves Andrade
Summary: The Internet of Things (IoT) has been widely used and has penetrated all areas of life. In the field of life sciences, it is gaining importance due to its cost-effectiveness in field research and transportation of sensors. This study proposes a real-time IoT water monitoring system that measures dissolved oxygen levels in the Pirapo River in southern Brazil, which supplies water to urban centers. The system can be used for monitoring and decision making in both urban and rural areas, providing timely information for safe decision making.
Article
Environmental Sciences
Janine M. Barr, Daphne Munroe, Julie M. Rose, Lisa Calvo, Kurt M. Cheng, Skylar Bayer, Danielle Kreeger
Summary: This study conducted field experiments to estimate seasonal oyster filtration physiology at oyster farms in three different bays in the Mid-Atlantic region and found that oyster physiological activity varied among farms and was influenced by environmental variables. The study provides a robust dataset and adds to the evidence supporting bivalve aquaculture as a nutrient reduction strategy.
ESTUARIES AND COASTS
(2023)
Article
Automation & Control Systems
Shang Gao, Guiyun Tian, Xuewu Dai, Qing Zhang, Zhiling Wang, Xinge Yang, Qiaomu Wang, Naishu Jia
Summary: This article introduces a lightweight FPGA-based wireless overpressure node for shock wave monitoring. Experimental tests validate its performance in dynamic parameters and network quality, showing lower error rates compared to wired systems.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2021)
Article
Engineering, Electrical & Electronic
Sunder Ali Khowaja, Parus Khuwaja, Kapal Dev, Muhammad Aslam Jarwar
Summary: In this study, we propose a PROMPT-based physical health monitoring framework that tracks subjective human behavior and handles the intensity variations associated with inertial measurement units. Experimental analysis shows that the proposed method achieves 14.56% better accuracy compared to existing works. We also propose a generalized framework for healthcare applications using wearable sensors and the PROMPT method for its triage with physical health monitoring systems in the real world.
IEEE SENSORS JOURNAL
(2023)
Review
Fisheries
Lisen Li, George Balto, Xiaoyan Xu, Yubang Shen, Jiale Li
Summary: This review integrates previous ecological studies to assess the feeding behavior and mechanisms of grass carp, revealing its impact on aquatic organisms and water quality.
REVIEWS IN AQUACULTURE
(2023)
Article
Computer Science, Hardware & Architecture
Sandra Sendra, Lorena Parra, Jose M. Jimenez, Laura Garcia, Jaime Lloret
Summary: This article proposes the design and implementation of a LoRa-based wireless sensor network for monitoring water quality in coastal areas, rivers, and ditches. The network consists of wireless sensor nodes equipped with various sensors to measure water quality parameters and weather conditions, with the data being sent to a storage database. The aim is to create an observatory that monitors the environment where the network is deployed.
MOBILE NETWORKS & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Swati Chopade, Hari Prabhat Gupta, Rahul Mishra, Aman Oswal, Preti Kumari, Tanima Dutta
Summary: This paper presents a sensor-based river water quality assessment system using deep neural network (DNN). The system estimates the water quality index (WQI) for labeling lab samples and uses automatic annotation technique to assign labels to sensory data instances. The labeled instances are then used to build a DNN classifier for predicting water quality. The system achieves high accuracy even with noisy labels.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Theory & Methods
Qinbao Xu, Elisa Bertino, Changda Wang
Summary: This paper introduces two provenance-based schemes, PIDP and PHP, for data trustworthiness assessment in wireless sensor networks. The results of experiments show that these two schemes outperform the DP scheme in terms of provenance compression rate and energy conservation rate, even in the case of unstable network topology.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2022)
Article
Agricultural Engineering
Mashud Rana, Ashfaqur Rahman, Joel Dabrowski, Stuart Arnold, John McCulloch, Bruno Pais
Summary: Water quality is a crucial factor affecting harvest outcome in freshwater ponds, with specific variables like dissolved oxygen, salinity, and temperature playing significant roles in the growth, survival, and yield of aquatic livestock. Machine learning methods were utilized to study the impact of water quality variations on prawn harvest outcomes, revealing dissolved oxygen, salinity, and temperature as key factors influencing overall harvest performance.
BIOSYSTEMS ENGINEERING
(2021)
Article
Chemistry, Analytical
Judith Santana Abril, Graciela Santana Sosa, Javier Sosa, Tomas Bautista, Juan A. Montiel-Nelson
Summary: This paper presents a novel charging method for underwater batteryless sensor node networks for oceanic fish farms, utilizing a distributed charging scheme and decentralized control process to reduce charging time. Experimental results demonstrate a significant improvement in charging efficiency.
Article
Engineering, Electrical & Electronic
Jaganathan Logeshwaran, Nallasamy Shanmugasundaram, Jaime Lloret
Summary: Recently, research on wireless personal area network (WPAN) has focused on network protocols, scheduling, and security, but resource utilization has been neglected. This paper presents a wireless resource utilization algorithm for a bi-partite scatternet, aiming to enhance bandwidth allocation and power utilization. The algorithm shows promising performance compared to existing algorithms in terms of reliability, throughput, collision probability, transmission probability, and SINR.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2023)
Article
Chemistry, Analytical
Sandra Viciano-Tudela, Lorena Parra, Paula Navarro-Garcia, Sandra Sendra, Jaime Lloret
Summary: This article proposes a new system for characterizing essential oils using low-cost sensor networks and machine learning techniques. The study found that using k-nearest neighbors algorithm, the accuracy, recall, F1-score, and precision values for identifying essential oils were 1, 0.99, 0.99, and 1, respectively.
Article
Chemistry, Analytical
Lorena Parra, Sandra Viciano-Tudela, David Carrasco, Sandra Sendra, Jaime Lloret
Summary: The paper presents a low-cost multiparametric probe that can be deployed in coastal areas and integrated into a wireless sensor network. The probe is composed of physical sensors capable of measuring water temperature, salinity, and total suspended solids (TSS). Calibration results show no effect of temperature on the sensors and no interference of salinity in the measuring of TSS or vice versa. The calibration models for salinity and TSS show good correlation coefficients and low mean absolute errors.
Article
Chemistry, Analytical
Ali Mohd Ali, Mohammad R. Hassan, Ahmad al-Qerem, Ala Hamarsheh, Khalid Al-Qawasmi, Mohammad Aljaidi, Ahmed Abu-Khadrah, Omprakash Kaiwartya, Jaime Lloret
Summary: This research paper investigates the spatial distributions of five different services (VoIP, VC, HTTP, and Electronic Mail) using three different approaches (circular, random, and uniform). It establishes a new algorithm to assess the real-time and best-effort services of IEEE 802.11 technologies and proposes a network prioritization framework for smart environments. The framework is validated using a simulation setting.
Article
Environmental Sciences
Faezeh Behzadi Pour, Lorena Parra, Jaime Lloret, Saman Abdanan Mehdizadeh
Summary: This paper investigates the speed and physical characteristics of fish using an online video-recording system and analyzes and predicts the data using YOLOv2 and an artificial neural network. The results show that the system has high accuracy and low error, allowing for continuous online monitoring of live fish and timely detection and diagnosis of their condition to prevent economic losses.
Article
Engineering, Electrical & Electronic
Jianchen Wang, Sandra Viciano-Tudela, Lorena Parra, Raquel Lacuesta, Jaime Lloret
Summary: This study develops a low-cost system using MQ sensors and Arduino Mega to monitor air quality in different scenarios, and identifies the origin of the data using discriminant analysis and probabilistic neural network. The results show that the proposed system achieves high accuracy in correctly classifying cases.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Abdulaziz Aldegheishem, Sandra Viciano-Tudela, Lorena Parra, Nabil Alrajeh, Jaime Lloret
Summary: This article proposes a wireless sensor network for monitoring the quality of reclaimed water for irrigation. The system uses sensor nodes and actuator nodes with LoRa technology. It focuses on developing sensors and evaluating the effect of capacitors on the sensor signal. The best configuration is determined based on several parameters, with configuration 3 being selected.
IEEE SENSORS JOURNAL
(2023)
Review
Chemistry, Analytical
Safa Hamdare, Omprakash Kaiwartya, Mohammad Aljaidi, Manish Jugran, Yue Cao, Sushil Kumar, Mufti Mahmud, David Brown, Jaime Lloret
Summary: The growing popularity of Electric Vehicles (EVs) is leading to a shift away from traditional gasoline-powered vehicles. As a result, there is an increasing demand for Electric Vehicle Charging Systems (EVCS) and the significant growth of EVCS as a public and private charging infrastructure. However, with the expanding network of EVCS, cybersecurity-related risks have also greatly increased. This paper provides a cybersecurity risk analysis of the EVCS network by examining recent advancements in EVCS, EV adaptation trends, charging use cases, vulnerabilities in infrastructure and protocols, possible cyber-attack scenarios, and real-time data analysis of EV charging sessions. It also highlights potential open research issues in EV cyber research for domain researchers and practitioners.
Article
Computer Science, Hardware & Architecture
Amjad Rehman, Ibrahim Abunadi, Khalid Haseeb, Tanzila Saba, Jaime Lloret
Summary: Artificial intelligence (AI) is experiencing significant growth in the areas of smart cities, agriculture, food management, and weather forecasting, primarily due to the limitations of computing power on sensing devices. The integration of AI with IoT and ubiquitous sensors has led to improvements in the agricultural sector and reduced management costs. However, optimizing resource management and data load for forwarding nodes near edge boundaries remains a challenging issue due to limited wireless technology resources.
COMPUTER STANDARDS & INTERFACES
(2024)
Article
Computer Science, Artificial Intelligence
Yun-Shan Wei, Jin-Fan Wang, Jia-Xuan Wang, Qing-Yuan Xu, Jaime Lloret
Summary: This article proposes an open-closed-loop iterative learning control (ILC) strategy for linear time varying multiple input multiple output (MIMO) systems with vector relative degree, where the time interval of operation depends on the number of iterations. A feedback control is introduced in the ILC design to compensate for the missing tracking signal caused by the iteration-dependent interval. The study shows that under certain assumptions, the ILC tracking error can converge to zero as the number of iterations tends to infinity. Additionally, the effectiveness of the developed method is illustrated through a simulation example.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Faeze Behzadipour, Mahmod Ghasemi Nezhad Raeini, Saman Abdanan Mehdizadeh, Morteza Taki, Bijan Khalil Moghadam, Mohammad Reza Zare Bavani, Jaime Lloret
Summary: Implementing intelligent irrigation and adjusting the system is crucial for modern agriculture. This study utilized data from sensors and image processing to analyze and optimize the irrigation system, resulting in an 11% water saving compared to traditional user-controlled irrigation.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Sandra Sendra, Lorena Parra, Jose M. Jimenez, Laura Garcia, Jaime Lloret
Summary: This article proposes the design and implementation of a LoRa-based wireless sensor network for monitoring water quality in coastal areas, rivers, and ditches. The network consists of wireless sensor nodes equipped with various sensors to measure water quality parameters and weather conditions, with the data being sent to a storage database. The aim is to create an observatory that monitors the environment where the network is deployed.
MOBILE NETWORKS & APPLICATIONS
(2023)
