Index

  • ACO, 311, 312
  • Activation function, defined, 139
  • Adaptation function, 141
  • Adaptive coefficient, defined, 138
  • Adaptive intelligence, 23
  • ADR, 302, 307, 309, 318, 319
  • Advanced metering infrastructure (AMI), 64
  • AED (automated external defibrillator), 354
  • AGC (automatic generation control), fuzzy logic and, 123
  • Agriculture, 254
  • AI, 304, 305
  • AI. see Artificial intelligence (AI)
  • Air conditioners for the laptop area (CRACS), 74
  • Alleles,
    • defined, 124
    • random values, 124
  • Ambubot, 354
  • Ambulance section, 361–362
  • Ambulance selection, 362
  • Ambulance(s),
  • AND network, 136–137
  • Android, 371, 372
  • Android application, 355, 356, 365
  • ANNs. see artificial neural networks (ANNs)
  • App, smart ambulance booking and tracking, 353, 356–358
  • Applications,
    • AI, 10, 21–23
    • ANNs, 144–145
    • genetic algorithm, 127
    • IoT technologies, 17
    • of IIoT, 19–20
  • Applications, IoT, 352–353
  • Applications of AI in the aviation industry, 220
  • Artificial intelligence, 95
  • Artificial intelligence (AI), IoT and, 5–15
    • AI concept, 6–10
    • applications, 10, 21–23
    • development of, 9
    • IoT concept, 10–15
    • operationalizing, benefits of, 9
    • overview, 5–6
    • principle of, 8
    • solutions, 7
  • Artificial intelligence of things (AIoT), 17
  • Artificial neural networks (ANNs),
    • applications, 144–145
    • back propagation algorithm, 133, 134–135
    • biological neuron, 128, 129–130
    • examples of,
      • AND operations, 136–137
      • OR operation, 137
      • XOR operation, 137, 138
    • feedforward network, 132–133
    • formal definition of, 130–131
    • forward propagation, 133–134
    • key components of, 138–141
      • error function and backpropagated value, 141
      • learning function, 141
      • output function–competition, 140–141
      • scaling and limiting, 140
      • summation function, 138–136
      • transfer function, 139–140
      • weighting factors, 138
    • learning laws,
      • delta rule, 143–144
      • gradient descent rule, 144
      • Hebb’s rule, 143
      • Hopfield law, 143
      • Kohonen’s learning law, 144
    • learning rates, 142–143
    • Mcculloch-Pitts model, 131, 136, 137
    • overview, 120, 121, 128–129
    • precise forecasting of price, advantages of, 145
    • recurrent networks, 132–133, 135–136
    • restructured power system, 144–145
    • Rosenblatt’s perceptron, 131–132
    • training, 141–142
      • supervised, 142
      • unsupervised, 142
  • Artificial neuron “temperature,” 140
  • Artificial neuron error, 141
  • ARTIK, 46
  • Assaults, 32, 36–41, 43–46
  • Attack, 32, 35, 37–45, 48–50, 53
  • Auditory perception, 7
  • Authenticity, 33
  • Automatic generation control (AGC), fuzzy logic and, 123
  • Autonomic computing, 356
  • Autonomous cars, 10
  • Availability, 33, 41, 43
  • AWS IoT, 47
  • Axons, 129
  • AZURE IoT, 47
  • Back propagation, 378
  • Back propagation algorithm, in ANNs, 133, 134–135
  • Backpropagated value, component of ANN, 141
  • Bacterial foraging optimization, 123
  • Baggage tracking, 254
  • Bariatric ambulance, 351
  • Barriers to IoT implementation, 215
  • Battery energy storage system (BESS), 123
  • Benefits of industrial IoT, 326
  • Big data, 6
    • analytics, illustration, 2, 3
    • delivering operational control possibilities, 4
    • driving technology of IoT, 13–14
    • IoT technologies with, 17
  • Biological neuron, 128, 129–130
  • Blockchain, 42, 51
  • Blockchain technology, IoT and, 15
  • Bluetooth technology, 12, 13
  • Boiler temperature sensor, in factory, 16
  • Boltzmann machines, 136
  • Bookings, ambulance. see smart ambulance booking and tracking systems
  • Building interactive robot systems, by AI technologies, 7
  • Building management systems (BMS), 74
  • Building on the lessons of 2020, 332
  • Bus-type ambulance, 351
  • Cancer studies, AI and, 8, 10
  • Cars,
    • autonomous, 10
    • connection to, illustration, 13
  • Challenges of wide-spread IIoT implementation, 329
  • Charity ambulance, 351
  • Cloud computing, 21–22, 371, 390, 391
    • infrastructure-as-a-service (IaaS), 92
    • knowledge discovery process, 95
    • platform-as-a-service (PaaS), 92
    • software-as-a-service (SaaS), 92
  • Cloud networking, system of, 353
  • Cloud server, 369, 373, 374
  • Commercial IoT, 322
  • Communication,
    • by proximity field, 12
    • IoT devices, 13, 14f
    • machine-to-machine, 17
    • online, 18
    • through technologies, 10
  • Comparison of wearable antenna designs, 168
  • Competition, component of ANN, 140–141
  • Computing process, 192
    • cloud computing, 194–195
    • distributed computing, 195–196
    • edge computing, 194
    • fog computing, 192–194
  • Confidentiality, 33, 36, 41, 43, 47, 50
  • Confirmation of booking, 363
  • Connected terminal units (RTUs), 67
  • Constrained application protocol (CoAP), 185–186
  • Consumer IoT, 322
  • Convolutional neural network (CNN), 283, 284
  • Coronavirus with IoT, can coronavirus be restrained?, 345
  • Correlation parameters, 377
  • Crossover, GA and, 124
  • Cryptography, 39, 46–48
  • Current technologies in aviation industry, 216
  • Cyber physical systems, 90
  • Cyber security, 7, 32, 46
  • DarkNet, 292, 293
  • Data collection,
    • mass, increase in, 5–6
  • Data protocols, 185
  • Data science, AI and, 8, 9
  • Data storage, 191–192
  • DDoS, 41, 43, 45
  • Declining demand for new projects/devices/services, 342
  • Decreased interest in consumer IoT devices, 338
  • Deep learning (DL), 5
  • Delta rule, 143–144
  • Dendrites, 129
  • Deployment of IoT applications, 218
  • Design of wearable antennas,
    • effect of substrate and ground geometries on antenna design, 154–159
    • embroidered antenna, 159–160
    • logo antennas, 159
    • wearable antenna based on electromagnetic band gap, 160–161
    • wearable reconfigurable antenna, 161–162
  • DHT11 sensor, 289
  • Digital diagnostics, 323
  • Digital divide widens, 343
  • Digital security, 15
  • Digital services, smart ambulance booking and tracking systems using IoT for. see Smart ambulance booking and tracking systems
  • Digital twins help with scenario planning, 339
  • Digital twins, 23–24
  • Disaster predication, 101, 103
  • Distributed energy resources (DER), 68
  • Distribution management system (DMS), 68, 80
  • DM, 302, 304, 307, 308, 319
  • ECDH, 46
  • Ecosystem, IoT, 15–21
  • Edge computing, 52
  • EDP, cost function of, 128
  • Effects of COVID-19 on industrial manufacturing, 332
  • Electric vehicle (EV), 64
  • Electrical airline logbook, 254
  • Emergency ambulance, 351–352
  • Emergency vehicle warning system, 355
  • Energy consumption regulators, 16
  • Energy management system (EMS), 68
  • Error function, component of ANN, 141
  • Euclidean distance, 379
  • Expert systems, AI and, 8
  • Facility management, IoT sensors, 19–20
  • Feedforward network, 132–133
  • Fiber optics, 13
  • Fibroblasts, 206–207, 212
  • Fog computing, 52
  • Forward propagation, in ANN, 133–134
  • Fractal antennas,
    • antenna design with defected semi-elliptical ground plane, 172
    • development of embroidered Sierpinski carpet antenna, 172–173
    • double-fractal layer wearable antenna, 172
    • Minkowski fractal geometries using wearable electro-textile antennas, 171
  • Fractional order fuzzy proportional-integral-derivative (FOFPID) controller, 123
  • Frequency vector, 377
  • Fuel emissions, 258
  • Fuel reduction, 276
  • Fulminant hepatic failure (FHF), 210
  • Fuzzy logic, 120–123
    • AGC, 123
    • basics, 122
    • microgrid wind, 123
    • overview, 120–121
    • power system and, 122
  • Fuzzy sets, 121
    • properties of, 122
  • GA, 308, 309
  • GC IoT, 48
  • GENCO, 145
  • General packet radio service (GPRS), 79
  • Generation rate constraint (GRC), 145
  • Genes, 124
  • Genetic algorithm (GA),
    • application, 127
    • crossover, 124–126
    • economic dispatch using, 128
    • important aspects, 124–126
    • overview, 120, 123–124
    • power system and, 127–128
    • standard, 126–127
  • Global positioning system (GPS), 10, 12, 64, 354, 356
  • Gradient descent rule, 144
  • Growth of aviation IoT industry, 224
  • GSM technology, 354
  • Health and safety monitoring, 330
  • Health data, 373–375, 384–387
  • Heating, ventilation, and air conditioning (HVAC), 74
  • Hepatocytes, 210
  • HMAC, 48
  • Home appliance managers, 16
  • Home area network (HAN), 80
  • Home page, smart ambulance booking and tracking systems, 360, 361
  • Hopfield law, 143
  • Hopfield models, 136
  • How IIoT is being used, 327
  • How is the Internet of Things converting the aviation enterprise?, 216
  • How the IoT Is improving the aviation industry, 219
  • HPVB (high priority vehicle booking), 366
  • Human activities as a source of pollutants, 230
  • Human ligament fibroblasts (HLF), 212–213
  • Human machine interfaces (HMIs), 67, 68
  • Hybrid neuro fuzzy (HNF) controller, 145
  • Hybrid particle swarm optimization (HCPSO), 145
  • Hydroxyapatite, 204–205, 212
  • IIoT. see Industrial internet of things (IIoT)
  • IIoT-supported safety for customers reduces liability for businesses, 331
  • Image processing technique, 354–355
  • Image recognition, 5, 8
  • Impact of COVID-19 on IoT applications, 337
  • Impact of COVID-19 on specific IoT technologies, 343
  • Impact of COVID-19 on technology in general, 341
  • Industrial analytics, 21
  • Industrial Internet of Things (IIoT), 63, 322
  • Industrial internet of things (IIoT), in industrial field,
    • AI, application of, 21–23
    • AI, IoT and, 5–15. see also Artificial intelligence (AI), IoT and
    • applications, 19–20
    • benefits, 20
    • challenges, 20
    • Industry 4.0
    • concept, 2–4, 18–19, 21–22
    • IoT ecosystem, 15–21
    • IoT vs., 3
    • overview, 2–5
    • trends, 23–24
  • Information,
    • access to, 4–5
    • analysis, 17
    • collection, 14, 22, 23
    • data-generating, 5
    • digitized, 2, 4, 18
    • exchange of, 11–13, 16, 23
    • from sources of public and private data, 7
    • technology in industry, 18
    • valuable, 19, 20
  • Information and communication technology (ICT), 60
  • Infrastructure,
    • application area of IoT, 352–353, 355
    • traffic lights, 353–356
  • Infrastructure IoT, 322
  • Integrating sensor and camera, 330
  • Integrity, 33, 36–37, 41–46
  • Intelligent analytics,
    • descriptive analytics, 100
    • predictive analytics, 100
    • prescriptive analytics, 100
  • Intelligent edge, 24, 24
  • Intelligent traffic signal control, 353–356
  • Interictal epileptiform discharges (IEDs), 67
  • Internet of Things (IoT), 59, 90, 93, 281, 283, 287, 290
  • Internet protocol (IP), 69
  • Interneuron, strength of, 131
  • Interoperability, challenge of IIoT, 20
  • Intrusion detection systems (IDS), 68
  • Inventory control, IoT sensors, 21
  • IoT adoption challenges, 218
  • IoT characteristics and measurement parameters, 233
  • IoT components, 189–191, 204
    • hardware, 190
    • middleware, 190
    • visualisation, 191
  • IoT networks largely unaffected, 343
  • IoT packet header, 184
  • IoT protocols, 183
  • IoT-based multimedia (IoTMM), 61
  • IR motion sensor, 292
  • Isotropic growth, 209
  • KDD, 302, 304
  • Keratinocytes, 206
  • Knowledge acquisition, AI and, 8
  • Knowledge representation methodologies, AI and, 8
  • Learning function, component of ANN, 141
  • Learning laws, ANNs,
    • delta rule, 143–144
    • gradient descent rule, 144
    • Hebb’s rule, 143
    • Hopfield law, 143
    • Kohonen’s learning law, 144
  • Learning methods,
  • Learning rates, ANNs, 142–143
  • Least mean square (LMS) learning rule, 144
  • LEO (low earth satellites), 75
  • Light-emitting diode (LED), 74
  • Limbal stem cell, 214
  • Limiting technique, component of ANN, 140
  • Literature survey, 209
  • LoRa-WAN, 32
  • LSE, 145
  • Machine learning (ML),
    • AI and, 5–7
    • back propagation, 97
    • computer vision, 89, 96
    • deep learning, 97
    • ensemble learning, 199
    • forms of, 8
    • natural language programming, 96
    • neural network, 199
    • reinforcement learning, 96–97, 198
    • reward, 98
    • supervised learning, 96, 197–198
    • unsupervised learning, 96–97, 198
  • Machine-to-machine (M2M), 4, 60
  • Machine-to-machine communication (M2M), 90
  • Main division to apply IoT in aviation, 205
  • Major challenges, 199–200
  • MATLAB software, 355
  • Medicine, AI in, 10
  • Mesenchymal stem cells (MSCs), 202, 205, 210, 213
  • Message queuing telemetry transport (MQTT), 187
  • Methodology or research design, 217
  • Microgrid wind, fuzzy, 123
  • Microsensors, 16
  • MIMO, 52
  • ML, 303, 309
  • Mobile data, 13
  • Models, neural network,
    • Hopfield models, 136
    • McCulloch-Pitts model, 131, 136, 137
    • Rosenblatt perceptron model, 131–132
  • Modern data centers, 191
  • MQ3 sensor, 287, 288
  • Multi-layer perceptron structure, ANNs, 131–132
  • Multiple-input multiple-output (MIMO), 77
  • Murine myoblast cell line, 219
  • Mutation, in genetic algorithms, 124
  • Myocardium, 210
  • National Institute of Standards and Technology (NIST), 73
  • Natural disasters,
  • Natural language processing (NLP), 5, 6, 8
  • Near-field communication (NFC), 74
  • Neighborhood area networks (NAN), 80
  • Network information service (NIS), 72
  • Neural networks, 5, 6
  • Neural networks (NNs). see Artificial neural networks (ANNs)
  • Neural stem cells, 220
  • Neurite outgrowth, 220–221
  • Neurites, 220
  • Neurons, defined, 128
  • New uses for drones, 339
  • NODEMCU, 290, 291, 293
  • Non-repudiation, 33, 41
  • N-point cross over technique, 125
  • Oauth, 48
  • Online booking system, for ambulance. see Smart ambulance booking and tracking systems Online retailers, 10
  • Online translators, 10
  • Operational efficiency, 225
  • Optimization,
    • ant colony optimization, 105
    • bacterial foraging, 123
    • genetic algorithms, 105
    • memetic algorithms, 105
    • particle swarm optimization, 105
    • problem, soft computing techniques (see Soft computing techniques)
    • Optimization in power system, fuzzy logic, 122, 123
      • genetic algorithm, 127–128
      • precise forecasting of price, ANN and, 145
  • OR network, 137
  • Osteoprogenitor cells, 205
  • Output function, component of ANN, 140–141
  • Oxygen cylinder facility, ambulance, 351
  • Patient transport ambulance, 351
  • Periodic metering units (PMUs), 67
  • Periosteum, 203
  • Photovoltaic (PV), 79
  • Pi camera, 287, 289, 290
  • PIR motion sensor, 281, 290
  • Plasma treatment, 203
  • Plug-in hybrid electric vehicle (PHEV), 70
  • Polynomial HMAC algorithm, 374, 379–381, 389–390
  • Postsynaptic neurons, 129
  • Potential of IoT in coronavirus like disease control, 345
  • Power system,
    • fuzzy logic and, 122, 123
    • genetic algorithm and, 127–128
    • precise forecasting of price, ANN and, 145
  • Precise forecasting of price, advantages of, 145
  • Predictive maintenance, 328
    • corrective maintenance, 100
    • preventive maintenance, 100, 103
  • Predictive maintenance for organizations that do the work, 332
  • Predictive maintenance model, 24
  • Presynaptic neurons, 129
  • Privacy, 32–33, 35–36, 38, 41, 46–47, 51
  • Programmable logic controller (PLC), 68
  • Protocols, 32, 40, 44, 52
  • PSO, 310, 311
  • Public key infrastructure (PKI), 42
  • Pyroelectric, 292
  • Radio frequency identification (RFID), 38–39, 71, 282, 283
  • Raspberry pi, 286, 287, 290–294
  • Real coded genetic algorithm (RCGA), 145
  • Recurrent neural networks, 132–133, 135–136
  • Re-epithelialization, 207
  • Regenerative medicine, 197
  • Remote monitoring, 323, 327
  • Renewable energy sources (RES), 70
  • Reproduction, GA and, 124
  • Required field of IoT in aviation, 206
  • Rest API, 187–189
  • Restructured power systems, using soft computing techniques,
  • Revolution of change (paradigm shift), 222
  • RFID technology, intelligent traffic signal control, 353, 355
  • Robot assistance, 323
  • Robotics, by AI, 7, 8
  • Role of IoT in COVID-19
  • response, 323
  • Rosenblatt’s perceptron, 131–132
  • SA, 303
  • Safety management,
    • disaster lifecycle, 102
    • mitigation, 102–104
  • Scaling method, component of ANN, 140
  • Security,
    • challenge of IIoT, 20
    • IoT machines, 15
  • Security threat, 32, 38–39, 41
  • Sensing and sampling of water treatment using IoT, 244
  • Sensor,
  • Sensors,
    • boiler temperature, 16
    • collecting information, 14
    • in tractors, 15–16
    • industrial analysis, 21
    • intelligent devices with, 13
    • microsensors, 16
    • refinement of, 17
    • smart, 11
  • Signup page, smart ambulance booking and tracking systems, 359, 360
  • Single-point crossover, 125
  • Smart airport, 255
  • Smart airport architecture, 211
  • Smart ambulance booking and tracking systems,
    • ambulance section, 361–362
    • ambulance selection, 362
    • confirmation of booking, 363
    • design, through App, 356–358
    • future scope, 366
    • home page, 360, 361
    • literature review, 353–356
    • overview, 350–353, 359
    • result and discussion, 363–365
    • sign up, 359, 360
    • use-case diagram, 357
    • welcome page, 358, 360
  • Smart city data platforms, 340
  • Smart grid (SG), 59
  • Smart home, concept of, 352
  • Smart refrigerator, 281–283, 286, 287
  • Smart sensors, 11
  • Smarter manufacturing for actionable insights, 333
  • Soft computing techniques, restructured power systems using,
  • Soil situation, sensors for, 16
  • Soma, 129
  • Specific IoT health applications surge, 340
  • Speech perception, 7, 8
  • SQP, non-linear programming method, 127–128
  • Standard deviation, 375
  • Streaming platforms, AI use,
    • transcribing audio, 10
    • video, 5, 10
  • String fitness value, 124
  • Summation function, component of ANN, 138–139
  • Supervised training/learning algorithm, 141, 142
  • Supervisory control and data acquisition (SCADA), 67
  • Supply chain monitoring, IoT sensors, 19–20
  • SVM, 303
  • Synapses, 129
  • System initialization, 241
  • Technology roadmaps get delayed, 344
  • Telehealth consultations, 323
  • Television TV, 68
  • Temperature, artificial neuron, 140
  • Textile antennas, 162–168
  • The Organization of Behavior: A Neuropsychological Theory (Hebb), 143
  • Topology, network,
    • defined, 131
    • feedforward and feedback, 132–133
    • for multi-layer perceptron, 131–132, 133
  • Track and trace solutions, 340
  • Tracking systems,
  • Traffic signal control, intelligent, 353, 354–356
  • Training, NNs, 141–142
    • supervised, 142
    • unsupervised, 142
  • Transfer function, component of ANN, 139–140
  • Transforming airline industry with internet of things, 219
  • Transmission and distribution (T&D), 75
  • Two-point crossover, 125–126
  • Types of antennas,
    • description of wearable antennas, 153–154
  • Ubiquitous, 70
  • Ultrasonic sensor, 285–288, 290–292, 294
  • Uniform crossover, 125, 126
  • Uninterruptible power supplies (UPS), 74
  • Unsupervised training/learning algorithm, 141, 142
  • Use of IoT during COVID-19, 321
  • Video streaming platforms, 5, 10
  • Visual object tagging tool, 292, 296
  • Visualization and management of the information, 243
  • Voice recognition technology, 366
  • Vulnerability, 37, 39–40
  • Wastewater and storm water monitoring using IoT, 241
  • Water management using IoT, 231
  • Water quality management based on IoT framework, 232
  • Water quality measuring sensors and data analysis, 239
  • Weighting factors, component of ANN, 138
  • Weights, defined, 131
  • Welcome page, of smart ambulance booking and tracking system, 358, 360
  • Wide area network (WAN), 80
  • Widrow-Hoff learning rule, 144
  • Wi-Fi, 10, 13
  • Wireless sensor network, 366, 370
    • spinneret, 199
    • syringe pump, 199–200
    • Taylor cone, 200
  • Wireless sensor networks (WSNs), 71
  • XOR network, 137, 138
  • X-ray digital images, 8
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