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Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/iot/index

Editor(s)-in-Chief: Der Jiunn Deng and Shancang Li

EAI Endorsed Transactions on Internet of Things is open access, a peer-reviewed scholarly journal focused on all areas related to the technologies and application fields related to the Internet of Things. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications on a quarterly frequency. Authors are not charged for article submission and processing.

INDEXING: DOAJ, CrossRef, Google Scholar, ProQuest, EBSCO, CNKI, Dimensions

The scope of the Transactions encompasses latest advances in the growing field of the Internet of Things (IoT), with the topics of interest being:

  • Technologies & Protocols: sensors, energy harvesters, RFID, machine-type communications, medium access protocols, radio resource management, industrial control, real-time systems, embedded software design.

  • Architectures & Services: cloud-based platforms, big data processing engines, security, privacy, device management, CPS/SCADA platforms, innovative/open service architectures, data mining, service middleware, semantic service management.

  • Applications & Use Cases: smart cities, smart buildings, smart traffic, industrial internet of things, smart metering, smart agriculture, etc.

  • Standardisation Landscape: IEEE, IETF, 3GPP, ETSI, and various alliances.

  • Experimentation & Prototypes: real-world deployments at scale, industrial deployments, experiences with prototypes (including what didn’t work), etc.

Call for Papers: Special issue on IoT, Machine Learning and Data Analytics for Smart Environment (Manuscript submission deadline: 2022-08-15; Notification of acceptance: 2022-09-30; Submission of final revised paper: 2022-10-30; Publication of special issue (tentative): 2023-01-01)

Lead Guest Editor: Mourade Azrour (Moulay Ismail University, Morocco) Guest Editor: Azeem Irshad (Faculty of Computer Science, Asghar Mall College Rawalpindi, HED, Govt. of the Punjab, Pakistan) Guest Editor: Azidine Guezzaz (Cadi Ayyad University, Morocco) Guest Editor: Jamal Mabrouki (Mohammed V University in Rabat, Faculty of Science, Morocco) Guest Editor: Said Benkirane (Cadi Ayyad University, Morocco;)

  • Editors-in-Chief
  • Der Jiunn Deng, National Changhua University of Education, Taiwan
  • Shancang Li, University of the West of England - UWE Bristol, UK
  • Area Editors
  • Antonella Molinaro (University Mediterranea of Reggio Calabria, Italy)
  • Atta Quddus (University of Surrey, UK)
  • Joachim Sachs (Ericsson, Sweden)
  • Kan Zheng (BUPT, China)
  • Liljana Gavrilovska (University Sts. Cyril and Methodius, Macedonia)
  • Maria Rita Palattella (University of Luxembourg, Luxembourg)
  • Rose Qingyang Hu (Utah State University, USA)
  • Xuan Liu (Future Network Research Center, Southeast University, China)
  • Chien-Liang Chen (Overseas Chinese University, Taichung, Taiwan)
  • Yu-Liang Liu (Overseas Chinese University, Taiwan)
  • Thomas Watteyne (INRIA, France; Linear Technologies, USA)
  • Pietro Manzoni (Universitat Politècnica de València)
  • Ahmet Çağdaş Seçkin (Uşak University, Turkey)
  • Xavi Vilajosana (UOC, Spain; Worldsensing, Spain)
  • Qindong Sun (Xi’an University of Technology, China)
  • Ripon Patgiri (National Institute of Technology Silchar, India)
  • Shanshan Zhao (University of West England, UK)
  • Kamran Ali (Beijing University of Posts & Telecommunications, China)
  • Muddesar Iqbal (London South Bank University, UK)
  • Yun Zhao (Shanxi Agricultural University, China)

  • Internet of Things and Wearable Devices: A Mixed Literature Review

    Appears in:
    IoT 24(4): e3

    Authors:
    Javier Gonzalez-Argote, Adrián Alejandro Vitón-Castillo, Carlos Alberto Gómez Cano, Verenice Sánchez Castillo, William Castillo-Gonzalez

    Published:
    4th Jul 2024

    Abstract:
    In recent years, the concept of the Internet of Things (IoT), its different models and emerging conceptual frameworks, have offered new opportunities for the integration of technologies into everyday life. Although initially based on the notion of the link between a physical device, its counterpart in a virtual environment and the technological aspects of that relationship, IoT-based wearable devices now offer multiple contributions to all types of users, from professionals and organizations to ordinary people. However, there are inaccuracies, abundant definitions, limited clarity in terms of trends, benefits, components, challenges and future lines of research. In this sense, a mixed literature review study was conducted. The mixed design, of dominant type (CUAN-qual), was composed of a quantitative analysis of bibliometric type and a qualitative analysis of thematic type and embedded in the first one. Data are provided on the main trends observed in the bibliometric indicators studied, a synthesis of some qualitative indicators of particular relevance and pertinence. In addition, future lines of research are presented to address strengths and challenges in this field.

  • Water Quality Estimation and Anomaly Detection: A Review

    Appears in:
    IoT 23(4): e2

    Authors:
    Seda Balta Kaç, Musa Balta, Süleyman Eken, Deniz Balta

    Published:
    18th Oct 2023

    Abstract:
    Critical infrastructures that provide irreplaceable services are systems that contain industrial control systems (ICS) that can cause great economic losses, security vulnerabilities and disruption of public order when the information in it is corrupted. These ICSs, which were previously isolated, have now become systems that contain online sensors, wireless networks and artificial intelligence technologies. This situation has also increased the scope of attacks by malicious people who intend to carry out industrial espionage and sabotage these systems. In this study, water quality estimation systems and anomaly detection are comprehensively examined. In this direction, the statistics of the studies in the literature, the methods for water quality anomaly detection, the existing data sets, and the difficulties encountered in the water systems to achieve better water management are discussed. Principle findings of this research can be summarized as follows: (i) new methodologies and architectures have improved water quality assessment through anomaly detection, (ii) different datasets including multi-modal information have been presented, and (iii) remaining challenges and prospects have been investigated.

  • Fortifying the Internet of Things: A Comprehensive Security Review

    Appears in:
    IoT 23(4): e1

    Authors:
    Oroos Arshi , Aryan Chaudhary

    Published:
    3rd Oct 2023

    Abstract:
    A variety of new technologies and their related capabilities have entered daily life in the long run of the IoT technology. Various industrial sectors, including healthcare, facility management, agriculture, energy, and transportation, use IoT technologies.  Interconnected networks are starting to include IoT devices like wearables, commercial appliances, connected electronics, smart grids, smart automobiles, etc. These gadgets produce enormous amounts of data, which are gathered, examined, recorded, and kept on the networks. IoT security is challenging to secure since the devices employ basic processors and operating systems that may not be compatible with advanced security measures. The information and the devices that are used by organizations as a part of their network must be protected against hackers. In this paper, we discuss about overall review of IoT systems that contains the scope of IoT in the  future era, Some of the characteristics of IoT systems, layers including the working Architecture of IoT. We will also discuss some of the vulnerabilities and surface area attacks, application areas regarding IoT. Potential weaknesses in the IoT system could cause serious issues for enterprises. The majority of Internet of Things (IoT) devices have security flaws, including incorrect physical security systems, lack of lock-out mechanisms, weak encryption schemes, improper key management systems, and improper authentication mechanisms, or the use of default credentials. As in the evolving era, security issues are becoming a major problem so some of the security threats of IoT are also mentioned here. This paper also provides the methods for addressing the vulnerabilities to IoT systems' security.

  • POX and RYU Controller Performance Analysis on Software Defined Network

    Appears in:
    IoT 23(3): e5

    Authors:
    Naimullah Naim, Amir Ullah Khan, Shabir Khan, Muhammad Bilal Afzal, Muhammad Abul Hassan, Muhammad Imad

    Published:
    5th Sep 2023

    Abstract:
    From the last decades different types of network schemes are pitched to enhance the user performance. Software Defined Networks (SDN) is also considered as important factor for different network schemes and its proper administration or management. Due to major deployment in today’s networking era SDN are further sub divided in to commercial and open-source controllers. Commercial and open-source controllers are utilized in different type of businesses. According to our knowledge considerable amount of literature is available on these controllers but did not provide or analyse performance of these controllers on different network parameters. This paper evaluates and compares the performance of two well-known SDN open-source controllers POX and RYU with two performance assessments. The first assessment is the implementation of optimal path by using Dijkstra's algorithm from source to destination. Second assessment is the creation of a custom topology in our desired tool (MiniNet emulator). Then, the performance in terms of QoS parameters such as Jitter, throughput, packet loss, and packet delivery ratio are computed by two end hosts in each network. After the assessments, the performance of POX are optimal as compare to the RYU and best suited to be deployed in any scenario.

  • Comprehensive survey study on fifth-generation wireless network and the internet of things

    Appears in:
    IoT 23(3): e3

    Authors:
    Arthur Nathaniel Mwang'onda, Menard Phiri

    Published:
    16th Aug 2023

    Abstract:
    Internet of Things is the interconnection of different components so that it should be able to communicate to each other to achieve a common goal. Therefore, for these components to communicate there will be a need of the communication Technologies. With the coming in of 5G wireless Network which provide more ability over the 2G,3G, 4G and other communication technologies. In this survey paper focuses much on what have been done before with 5G wireless Network in relation to Internet of Things, Application of 5G IoT, it also describes the various challenges which may arise when implementing it and the research questions. The next-generation protocol that will help to alleviate the current challenges which have been encountered. This paper will analyze the comprehensive survey on fifth-generation wireless network and Internet of Things from different papers and this will help to map the way forward on what best can apply 5G and other protocols in Internet of things.

  • Cyber Attacks Classification on Enriching IoT Datasets

    Appears in:
    IoT 23(3): e2

    Authors:
    Meltem Kurt Pehlivanoglu, Nassima Yousef Saleem Al Zubaidi, Alend Hasan Jarjis

    Published:
    4th Aug 2023

    Abstract:
    In the era of the 5.0 industry, the use of the Internet of Things (IoT) has increased. The data generates from sensors through IoT industrial systems, any fault in those systems affects their performance and leads to real disaster. Protecting them from any possible attacks is an essential task. to secure any system, it needs to predict in the first place possible attacks and faults that could happen in the future. Predicting and initiating the attack type and the accuracy of these predictions can be done with machine learning models nowadays on the datasets produced with IoT networks. This paper classifies several attacks type based on several criteria and techniques to enhance the performance of machine learning (ML) models such as Voting techniques beside six ML models; Random Forest (RF), Decision Tree (DT), K-nearest neighbor (KNN), Support Vector Machine (SVM), Logistic regression (LR), and eXtreme Gradient Boosting (XGBoost) using Enriching IoT dataset. The results showed that 100% accuracy was achieved in estimating process with the XGBoost model.    

  • Weed detection with Improved Yolov 7

    Appears in:
    IoT 23(3): e1

    Authors:
    Qiyuan Xue, Mingkang Peng, Fuzhong Li, Wuping Zhang, Jialiang Yuan, Peipu An

    Published:
    31st Jul 2023

    Abstract:
    INTRODUCTION: An improved Yolo v7 model. OBJECTIVES: To solve the weed detection and  identification in complex field background. METHODS: The dataset was enhanced by online data enhancement, in which the feature extraction, feature fusion and feature point judgment of weed image were carried out by Yolov7 to predict the weed situation corresponding to the prior box. In the enhanced feature extraction part of Yolov7, CBAM, an attention mechanism combining channel and space, is introduced to improve the attention of the algorithm to weeds and strengthen the characteristics of weeds. RESULTS: The mean average precision (mAP ) of the improved algorithm reached 91.15%, which was 2.06% higher than that of the original Yolov7 algorithm. Compared with the current mainstream target detection algorithms Yolox, Yolov5l, Fster RCNN, Yolov4-tiny and Yolov3, the mAP value of the improved algorithm increased by 4.35, 4.51, 5.41, 19.77 and 20.65 percentage points. Weed species can be accurately identified when multiple weeds are adjacent. CONCLUSION: This paper provides a detection model based on Yolov7 for weed detection in the field, which has a good detection effect on weed detection, and lays a research foundation for intelligent weeding robot and spraying robot.

  • ResNet-based dairy daily behavior recognition

    Appears in:
    IoT 23(2): e5

    Authors:
    F. Z. Li, Lijun Cheng, T. H. Duan, C. Jing

    Published:
    31st Jul 2023

    Abstract:
    With the rapid development of China ’s dairy farming industry, it becomes difficult to breed and manage the increasing number of dairy cows. The smart agricultural enabled by edging techniques such as smart sensor, IoT, machine learning, etc. shows great potential to improve the scientific breeding and management of dairy cows. Using machine learning assisted computer vision to identify and classify the behavior of dairy cows can quickly determine the health status of dairy cows and improve management efficiency. However, there are still some challenges need to be addressed in the current behavior recognition of dairy cows. Due to the more complex background of dairy farms, the increase in the number of cows makes the mutual shading problem of dairy cows serious, which leads to the low efficiency of dairy cow behavior recognition. To address this challenge, this paper collected and labeled four types of 1,660 dairy daily behavior datasets and proposed a residual neural network (ResNet)-based dairy daily behavior recognition model. Experiments show that the proposed method is far superior to the baseline method in accuracy performance, and it provides inspiration for the behavior recognition of cows.

  • Fast selective encryption algorithms based on moments and chaos theory

    Appears in:
    IoT 23(2): e3

    Authors:
    Abdelhalim Kamrani, Said Najah, Khalid Zenkouar

    Published:
    24th Jul 2023

    Abstract:
    In this work, we introduce a novel selective encryption scheme based on chaos theory and moments transforms, two moments families were considered namely Tchebichef and Hahn. The goal is to propose a fast and secure encryption scheme that can be deployed in real world scenarios. The proposed algorithms operate in the transform domains of Tchebichef and Hahn moments. We encrypt only the most significant coefficients of the moments transforms. First, we down sample the computed moments’ matrices coefficients, then we use two logistic maps for confusion and diffusion of the down-sampled Tchebichef’s and Hahn’s coefficients, the resulting matrix is the encrypted image. This approach improves drastically the time performance of the encryption algorithm while keeping a “good” security level. In order to prove the performance of our algorithms, we run different experiments and test the algorithms on different criteria: MSE, correlation coefficient, differential analysis, entropy and time performance. The presented results prove that the encryption algorithms proposed are secure and outperform state-of-the-art algorithms.

  • Flood Monitoring and Early Warning Systems – An IoT Based Perspective

    Appears in:
    IoT 23(2): e4

    Authors:
    Dr Tasneem Ahmed, Mohammad Shahid Husain, Mohammed Siddique

    Published:
    24th Jul 2023

    Abstract:
    One of the most frequently occurring calamities around the world is the flood. For flood prone areas or countries, an essential part of their governance is flood management. The necessity to continuously review and analyse the adverse or ambient environmental conditions in real-time demands developing a monitoring system so that floods could be detected beforehand. This paper discusses different Internet of Things (IoT) based techniques and applications implemented for efficient flood monitoring and an early warning system and it is observed that in future, the combination of IoT and Synthetic Aperture Radar (SAR) data may be helpful to develop robust and secure flood monitoring and early warning system that provides effective and efficient mapping during natural disasters. The emerging technology in the discipline of computing is IoT, an embedded system that enables devices to gather real-time data to further store it in the computational devices using Wireless Sensor Networks (WSN) for further processing. The IoT based projects that can help collect data from sensors are an added advantage for researchers to explore in providing better services to people. These systems can be integrated with cloud computing and analyzing platforms. Researchers recently have focussed on mathematical modeling based flood prediction schemes rather than physical parametric based flood prediction. The new methodologies explore the algorithmic approaches. There have been many systems proposed based on analog technology to web-based and now using mobile applications. Further, alert systems have been designed using web-based applications that gather processed data by Arduino Uno Microcontroller which is received from ultrasonic and rain sensors. Additionally, the machine learning based embedded systems can measure different atmospheric conditions such as temperature, moisture, and rains to forecast floods by analyzing varying trends in climatic changes.

  • IoT-Q-Band: A low cost internet of things based wearable band to detect and track absconding COVID-19 quarantine subjects

    Appears in:
    IoT 20(21): e5

    Authors:
    Vibhutesh Kumar Singh, Kumar Utkarsh, Nidhi Upadhyay, Sujeet Kumar, Himanshu Chandna, Ashish Kumar

    Downloads:
    6891

    Abstract:
    The world health organization (WHO) has declared the novel coronavirus disease (nCoV or COVID-19) outbreak a pandemic, and quarantines are playing a vital role in containing its spread. But globally, the defections of the quarantined subjects are raising serious concerns. If COVID-19 positive, the absconding quarantine subjects can infect more people, which makes the timely detection of them vital. As the literature suggests, a wearable makes a subject more compliant towards healthcare routines/restrictions; thus, in this work, we have designed an IoT based wearable quarantine band (IoT-Q-Band) to detect the absconding. While designing it, we kept in mind the cost, global supply chain disruption, and COVID-19 quarantine duration, which the WHO recommends. This wearable prototype, with the bundled mobile app, reports and tracks the absconding quarantine subjects in real-time. IoT-Q-Band is an economical solution that could benefit lowincome regions to prevent the spread of COVID-19.

  • Analysis of Indoor Rowing Motion using Wearable Inertial Sensors

    Appears in:
    IoT 15(6): e1

    Authors:
    Paul Havinga, Lennart Buit, Stephan Bosch, Muhammad Shoaib, Nirvana Meratnia, Stephen Geerlings

    Downloads:
    6553

    Abstract:
    In this exploratory work the motion of rowers is analyzed while rowing on a rowing machine. This is performed using inertial sensors that measure the orientation at several positions on the body. Using these measurements, this work provides a preliminary analysis of the differences between experienced and novice rowers, or between a good and a bad technique. The analysis shows that the measured postural angles show no clear trend that would set apart experienced and novice rowers or a bad and a good technique. However, there are clear differences in absolute postural angle's consistency and timing consistency of strokes between novice and experienced rowers. We also applied a machine learning technique to the data to find the similarities between different rowers and an experienced reference rower. The results can be used to compare the quality of the rowing technique with respect to a reference. In this paper, we present our initial results as well as the challenges that need to be further explored.

  • UV Disinfection Robot with Automatic Switching on Human Detection

    Appears in:
    IoT 20(23): e1

    Authors:
    Ch. Sesha Sai Hamsika, A. Naga Sri Manasa, P. Shalini, A. Vyshnavi

    Downloads:
    6450

    Abstract:
    Ultra violet (UV) light is used for the purpose of disinfection or sterilization of rooms and surfaces. UV-C is employed as it has germicidal properties, in particular - bacteria and viruses, but it is detrimental to human-beings as well. So, for the purpose of disinfection without human interference, a UV Robot has been designed and implemented that follows a pre-defined path. It was equipped with three 20W UV lamps which radiates light in all directions. Given that UV light can be dangerous to humans, an embedded system based on Arduino along with PIR sensors are employed on top of the robot that detects human or animal’s motion and presence. So, one of the effective ways to avoid getting infected with SARS-COV-2 (Corona virus) is by sterilizing rooms using UV robot.

  • QR Code based Indoor Navigation system for Attender Robot

    Appears in:
    IoT 20(21): e3

    Authors:
    A. Sneha, Tusar Kanti Mishra, V. Sai Lakshmi Teja, Kuppili N. Satya Chitra

    Downloads:
    5614

    Abstract:
    In this paper, we elicit a cost-effective design of a robot that is used to perform the tasks of the attender, a wheeled mobile robot. The two main challenging aspects of mobile robotics are to achieve localization and navigation. Localization determines the location of the robot with respect to its environment. Navigation is the movement of the robot from one location to the other. Here, the unique design and representation of the QR code helped us to localize and navigate the robot. A raspberry pi mounted with a camera is used to interface with the robot. The triangulation method is used to localize the robot. Dijkstra’s algorithm is used to compute the shortest path from source to destination. The system is monitored tested based on the feedback system established by the Hologram cellular USB modem. Experimental results show that this approach has good feasibility and effectiveness. The robot navigates through the shortest path, performs specified tasks, and returns to its source.

  • Design and Implementation of a Wireless Sensor Network for Agricultural Applications

    Appears in:
    IoT 18(16): e1

    Authors:
    Jobish John, V. Ramulu, Gaurav S. Kasbekar, Maryam Shojaei Baghini, Dinesh K. Sharma

    Downloads:
    4531

    Abstract:
    We present the design and implementation of a shortest path tree based, energy efficient data collection wireless sensor network to sense various parameters in an agricultural farm using in-house developed low cost sensors. Nodes follow a synchronized, periodic sleep-wake up schedule to maximize the lifetime of the network. The implemented network consists of 24 sensor nodes in a 3 acre maize farm and its performance is captured by 7 snooper nodes for different data collection intervals: 10 minutes,1 hour and 3 hours. The almost static nature of wireless links in the farm motivated us to use the same tree for a long data collection period (3 days). The imbalance in energy consumption across nodes is observed to be very small and the network architecture uses easy-to-implement protocols to perform different network activities including handling of node failures. We present the results and analysis of extensive tests conducted on our implementation, which provide significant insights.

  • A Review on Smart Helmet for Accident Detection using IOT

    Appears in:
    IoT 19(20): e3

    Authors:
    H.T. Chethana, M. Hamsaveni, H.C. Impana

    Downloads:
    3474

    Abstract:
    As we know that accidents are increasing day by day, we can also notice that many laws and regulations are posed by government in order to avoid this accidents. Accidents can be defined as the unplanned event or the mistake that may occur resulting in injury and sometimes it also leads to death. The accidents in case of two wheelers are more compared to other vehicles. This may be avoided by wearing helmets and riding vehicles without consuming alcohol. This survey is on smart helmet for accidence avoidance and also examining various related techniques. This research also helps us to understand IOT technology which is being emerged now a days. From the literature survey we find that the method proposed using microcontroller RF transmitter and other sensors is cost effective but we find the system proposed using Raspberry pi module, Pi camera, Pressure Sensor, GPS system which uses image processing algorithms is most efficient since the image processing is included so that we can easily detect the use of helmet from the rider. Smart helmet system helps to provide safety and security to the two wheeler riders.

  • Systematic Literature Review on the Accuracy of Face Recognition Algorithms

    Appears in:
    IoT 22(30): e5

    Authors:
    Rogério Rossi, Kechi Hirama, Marcos Agenor Lazarini

    Downloads:
    3388

    Abstract:
    Real-time facial recognition systems have been increasingly used, making it relevant to address the accuracy of these systems given the credibility and trust they must offer. Therefore, this article seeks to identify the algorithms currently used by facial recognition systems through a Systematic Literature Review that considers recent scientific articles, published between 2018 and 2021. From the initial collection of ninety-three articles, a subset of thirteen was selected after applying the inclusion and exclusion procedures. One of the outstanding results of this research corresponds to the use of algorithms based on Artificial Neural Networks (ANN) considered in 21% of the solutions, highlighting the use of Convolutional Neural Network (CNN). Another relevant result is the identification of the use of the Viola-Jones algorithm, present in 19% of the solutions. In addition, from this research, two specific facial recognition solutions associated with access control were found considering the principles of the Internet of Things, one being applied to access control to environments and the other applied to smart cities.

  • Dedicated networks for IoT: PHY / MAC state of the art and challenges

    Appears in:
    IoT 15(1): e3

    Authors:
    J. M. Gorce, C. Goursaud

    Downloads:
    2658

    Abstract:
    This paper focuses on the the emerging transmission technologies dedicated to IoT networks.We first analyze the classical cellular network technologies when taking into account the IoT requirements, and point out the need of dedicated technologies for IoT. Then, we present the PHY and MAC layers of the technologies that are already deployed, or likely to be deployed: UNB by SigFox, CSS by LoRaTM,Weighless, and RPMA by Ingenu. We then compare their performances to highlight their pros and cons. Finally, we discuss on the open research challenges that still need to be addressed.

  • IoT-F2CDM-LB: IoT Based Fog-to-Cloud and Data-in-Motion Architectures with Load Balancing

    Appears in:
    IoT 18(13): e1

    Authors:
    Emad H. Al-Hemiary, Istabraq M. Al-Joboury

    Downloads:
    2503

    Abstract:
    The work in this paper tries to enhance the performance of IoT by modifying the Cloud based architecture in terms of storage, processing, and Load Balancing (LB). The assumption is as follows: In a single Fog server, high traffic coming from Things may cause packet loss which in turn affect the overall IoT performance. To overcome such a situation, LB on Fog layer is proposed and implemented practically using virtualization technology. The proposed IoT based Fog-To-Cloud and Data-inMotion with LB (IoT-F2CDM-LB) architecture consists of two load balancers; HAProxy and Server Load Balancing (SLB), are used to distribute messages from Things to four virtualized Fog servers according to Least Connection technique. The implementation is carried out using VirtualBox and GNS3. Message Queue Telemetry Transport (MQTT) protocol is used to transfer messages between layers. Both load balancers result in packet loss reduction by 50%, lower response time and higher throughput.

  • Flood Monitoring and Early Warning Systems – An IoT Based Perspective

    Appears in:
    IoT 23(2): e4

    Authors:
    Dr Tasneem Ahmed, Mohammad Shahid Husain, Mohammed Siddique

    Downloads:
    2487

    Abstract:
    One of the most frequently occurring calamities around the world is the flood. For flood prone areas or countries, an essential part of their governance is flood management. The necessity to continuously review and analyse the adverse or ambient environmental conditions in real-time demands developing a monitoring system so that floods could be detected beforehand. This paper discusses different Internet of Things (IoT) based techniques and applications implemented for efficient flood monitoring and an early warning system and it is observed that in future, the combination of IoT and Synthetic Aperture Radar (SAR) data may be helpful to develop robust and secure flood monitoring and early warning system that provides effective and efficient mapping during natural disasters. The emerging technology in the discipline of computing is IoT, an embedded system that enables devices to gather real-time data to further store it in the computational devices using Wireless Sensor Networks (WSN) for further processing. The IoT based projects that can help collect data from sensors are an added advantage for researchers to explore in providing better services to people. These systems can be integrated with cloud computing and analyzing platforms. Researchers recently have focussed on mathematical modeling based flood prediction schemes rather than physical parametric based flood prediction. The new methodologies explore the algorithmic approaches. There have been many systems proposed based on analog technology to web-based and now using mobile applications. Further, alert systems have been designed using web-based applications that gather processed data by Arduino Uno Microcontroller which is received from ultrasonic and rain sensors. Additionally, the machine learning based embedded systems can measure different atmospheric conditions such as temperature, moisture, and rains to forecast floods by analyzing varying trends in climatic changes.
Publisher
EAI
ISSN
2414-1399
Number of Volumes
9
Last Published
2023-10-02
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