LEADER 09912nam 2200481 450 001 996464545303316 005 20231110231454.0 010 $a3-030-96466-3 035 $a(MiAaPQ)EBC6896795 035 $a(Au-PeEL)EBL6896795 035 $a(CKB)21325478200041 035 $a(PPN)260825875 035 $a(EXLCZ)9921325478200041 100 $a20221006d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aInternet of Things : technology and applications $e4th IFIP International Cross-Domain Conference, IFIPIoT 2021, virtual event, November 4-5, 2021, revised selected papers /$fedited by Luis M. Camarinha-Matos, [and three others] 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$d©2022 215 $a1 online resource (271 pages) 225 1 $aIFIP Advances in Information and Communication Technology ;$vv.641 311 08$aPrint version: Camarinha-Matos, Luis M. Internet of Things. Technology and Applications Cham : Springer International Publishing AG,c2022 9783030964658 320 $aIncludes bibliographical references and index. 327 $aIntro -- Preface -- Organization -- Contents -- Summary of Challenges -- Challenges in IoT Applications and Research -- 1 Introduction -- 2 Challenges in IoT Applications -- 2.1 Scope -- 2.2 Main Engineering Challenges in IoT Development -- 2.3 Critical Success Factors in Advanced IoT Applications -- 2.4 Futuristic Application Scenarios for the Next 5-10 Years -- 2.5 Concluding Remarks -- 3 Challenges in IoT Research -- 3.1 Scope -- 3.2 Main Current IoT Research Challenges -- 3.3 Promising Approaches to Face the Challenges -- 3.4 Emerging Technologies that are Likely to Have an Impact in the Next 5-10 Years -- 3.5 Concluding Remarks -- 4 Conclusions -- References -- Modernizing Agricultural Practice Using IoT -- sFarm: A Distributed Ledger Based Remote Crop Monitoring System for Smart Farming -- 1 Introduction -- 2 Related Research Overview -- 3 Novel Contributions -- 3.1 Problems Addressed in the Current Paper -- 3.2 Novel Solutions Proposed -- 4 Is the Distributed Ledger a Feasible Solution? -- 5 Architectural Overview of sFarm -- 5.1 Sensing Nodes -- 5.2 Edge Node -- 6 Proposed Algorithm for sFarm -- 7 Implementation and Validation -- 7.1 Implementation -- 7.2 Agriculture Datasets and Community Data Sharing Using the Proposed sFarm -- 7.3 sFarm Validation -- 8 Conclusions and Future Research -- References -- Smart Agriculture Using Flapping-Wing Micro Aerial Vehicles (FWMAVs) -- 1 Introduction -- 2 Smart Agriculture Using IoT-Related Work -- 3 Smart Agriculture Using Beebots-Proposed Vision -- 4 Proposed Beebot -- 4.1 The Exoskeleton -- 4.2 The Wings -- 4.3 Actuation -- 4.4 Transmission -- 4.5 Weight Shifting Mechanism -- 5 Proposed Design -- 5.1 System Dynamics -- 5.2 Actuator Command Generation -- 5.3 Weight Shifting Mechanism -- 5.4 Attitude Controller -- 5.5 Position Controller -- 5.6 ROS and Simulation -- 6 Experimental Results. 327 $a6.1 Flight -- 6.2 Hover -- 6.3 Tilt -- 7 Conclusions and Future Work -- References -- Smart Lysimeter with Crop and Environment Monitoring -- 1 Introduction -- 2 Smart Lysimeter Architecture -- 3 Experimental Prototype -- 3.1 Lysimeter Module -- 3.2 Camera Module -- 3.3 Lysimeter Software -- 4 Experimental Results -- 5 Conclusions -- References -- Cyber-Physical IoT Systems in Wildfire Context -- Fuel Break Monitoring with Sentinel-2 Imagery and GEDI Validation -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Areas -- 2.2 Data and Tools -- 2.3 Time Series Generation -- 2.4 Fuel Treatments Detection -- 2.5 Fuel Load Growth Estimation -- 2.6 Error Estimation -- 3 Results -- 3.1 Fuel Treatment Detection Results -- 3.2 Fuel Load Growth Estimation -- 4 Discussion -- 5 Conclusion and Future Work -- References -- A Study on Small Sensor Node Antenna Performance Camouflaged Under Grassland Fire -- 1 Introduction -- 2 Sensor Node Antenna -- 3 Scenario Definition and Case Studies -- 4 Simulation Results and Discussion -- 5 Conclusions -- References -- A Data Fusion of IoT Sensor Networks for Decision Support in Forest Fire Suppression -- 1 Introduction -- 2 A Data Fusion Based DSS High-Level Architecture -- 3 Mobile Application -- 4 The CPS-IoT Multi-sensor Node -- 5 Conclusions -- References -- Drones as Sound Sensors for Energy-Based Acoustic Tracking on Wildfire Environments -- 1 Introduction -- 2 Related Work -- 2.1 UAVs for Wildfire Detection, Prevention and Monitoring -- 2.2 Acoustic Localization -- 3 Problem Formulation and Characterization -- 4 the Proposed Methodology -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- IoT for Smart Health -- cStick: A Calm Stick for Fall Prediction, Detection and Control in the IoMT Framework -- 1 Introduction -- 2 Related Prior Research. 327 $a2.1 Major Issues with the Existing Solutions -- 3 Novel Contributions -- 4 Physiological Parameters Considered in cStick -- 4.1 Grasping Pressure -- 4.2 Dietary Habits -- 4.3 Posture -- 4.4 Blood Oxygen Levels -- 4.5 Irregular Heart Beats per Minute -- 4.6 Surroundings of the User -- 4.7 Location of the User -- 5 Architectural Flow for Fall Prediction and Detection in cStick -- 5.1 Physiological Sensor Data Unit -- 5.2 Parameter Analysis Unit -- 5.3 Fall Prediction and Detection Unit -- 5.4 Control Unit -- 6 Design Flow for Fall Prediction and Detection in cStick -- 7 Implementation and Validation for Fall Prediction and Detection in cStick -- 7.1 Physiological Data Acquisition -- 7.2 Machine Learning Model for Edge Computing Used in cStick -- 7.3 Real-Time IoMT-Edge Computing Validation in cStick -- 8 Conclusions and Future Research -- 8.1 Conclusions -- 8.2 Future Research -- References -- Hardware/Software Co-Design of a Low-Power IoT Fall Detection Device -- 1 Introduction -- 2 Fall Detection Basic Principles -- 3 Platform Architecture -- 3.1 Platform Overview -- 3.2 Device Hardware Architecture -- 3.3 3D Printed Enclosure -- 3.4 Device Operation Algorithm -- 3.5 Post-Fall Algorithm -- 4 Evaluation -- 5 Discussion -- 6 Conclusion -- References -- Security -- ReOPUF: Relaxation Oscillator Physical Unclonable Function for Reliable Key Generation in IoT Security -- 1 Introduction -- 2 IoT Node Authentication with PUFs - Motivation -- 3 Related Research -- 3.1 Ring Oscillator PUF -- 3.2 Arbiter PUF -- 3.3 PUF Quality Metrics -- 4 Proposed Relaxation Oscillator PUF (ReOPUF) -- 5 Experimental Results -- 5.1 Evaluation of PUF Quality Metrics -- 6 Security Evaluation of the Proposed PUF -- 6.1 Entropy Analysis -- 6.2 Correlation Coefficient Analysis -- 6.3 Power Analysis of ReOPUF -- 7 Conclusion -- References. 327 $aCyber-Physical Application for the Safety and Security Enforcement in Oil and  Gas Transportation -- 1 Introduction -- 2 State of the Art -- 2.1 State of the Art of Tank Truck Automation -- 2.2 Cyber-Physical Systems -- 3 System Architecture -- 3.1 Vehicle Node -- 3.2 Data Flow Management Platform -- 3.3 Applications -- 4 Application Logic -- 4.1 Office Operations -- 4.2 On-Field Operations -- 5 Implementation Notes -- 5.1 Application Interfaces -- 5.2 Application Graphical User Interfaces -- 5.3 Logic Implementations -- 6 Experimental Results -- 6.1 Performance Indicators -- 6.2 Application Impact -- 7 Privacy Issues -- 8 Concluding Remarks -- References -- A Secure and Efficient Cloud-Connected Body Sensor Network Platform -- 1 Introduction -- 2 Background -- 2.1 Body Sensor Networks -- 2.2 Data Privacy and Security -- 2.3 Data Compression -- 3 Methodology -- 3.1 Platform Design -- 3.2 Compression -- 3.3 Encryption -- 3.4 Cloud Uploading and Processing -- 3.5 Experimental Setup -- 4 Results and Discussion -- 4.1 Compression -- 4.2 Packet Processing Efficiency -- 5 Conclusion -- References -- Methods -- EasyDeep: An IoT Friendly Robust Detection Method for GAN Generated Deepfake Images in Social Media -- 1 Introduction -- 2 Challenges of GAN Generated Deepfake Images -- 3 Novel Contributions of the Current Paper -- 4 Related Prior Works -- 5 Analysis of GAN Generated Deepfake Images -- 5.1 Entropy Computation -- 5.2 Haralick's Texture Features Analysis -- 5.3 Histogram Analysis -- 6 The Proposed Novel Deepfake Detection Method at Edge Computing Platform -- 6.1 System Level Representation -- 6.2 Detection Methodology at the Edge Platform -- 6.3 Phases of Detection Method -- 6.4 Detection API -- 6.5 Detection Metrics -- 7 Experiments -- 7.1 Datasets -- 7.2 GAN Generated Image Analysis. 327 $a7.3 Implementation of Proposed Detection Method of GAN Generated Images at an Edge Computing Platform -- 8 Results -- 8.1 Analysis of GAN Generated Images -- 8.2 Evaluation of Edge Detection Model -- 9 Conclusion and Future Work -- References -- A Fuzzy Logic Approach for Self-managing Energy Efficiency in IoT Nodes -- 1 Introduction -- 2 Related Work -- 3 Energy Consumption in IoT Nodes -- 4 Fuzzy Logic System for Energy Efficiency -- 5 Fuzzy Logic System for Energy Efficiency -- 5.1 Application of the Fuzzy Logic System -- 5.2 Analysis of Results -- 6 Conclusions -- References -- Hydric Resources and Meteorological Monitoring IoT System -- 1 Introduction -- 2 A Review of IoT Based Surface Water Quality Monitoring Systems -- 3 System Architecture -- 4 Software Setup -- 5 Conclusions -- References -- Author Index. 410 0$aIFIP Advances in Information and Communication Technology 606 $aInternet of things 615 0$aInternet of things. 676 $a004.678 702 $aCamarinha-Matos$b Luis 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996464545303316 996 $aInternet of Things : technology and applications$92920126 997 $aUNISA