TekSummit

Hosted by The GAO Group of Companies

TekSummit

Hosted by GAO Research Inc.
IoT & M2M Research & Development
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About TekSummit

The GAO (Global Advanced Operations) Group started TekSummit in the year of 2021. It was an instant success. We ran it for 3 years, 2021, 2022, and 2023. We had hundreds of highly qualified speakers and thousands of attendees. We paused TekSummit in 2024 so that we could focus on our fast-growing businesses.

We have restarted it in 2025 and where continue the success!

Below are partial lists of the past speakers and presentations.

Furthermore, to accelerate the expansion of our thriving businesses in our main market, namely North America, we are very actively seeking corporate partners and individual consultants who are located in the U.S. or Canada. For the corporate partnership, please click here. For individual consultants (also job seekers with lots of work experience), please click here. 

TekSummit Hosted by Other 2 Member Companies of The GAO Group

TekSummit – Hosted by GAO Tek Inc.

  • IoT & M2M
  • IoT & M2M for Manufacturing
  • IoT & M2M for Construction
  • IoT & M2M for Healthcare
  • IoT & M2M for Agriculture
  • IoT & M2M for Smart Cities
  • IoT & M2M for Automotive & Transportation
  • IoT & M2M for Oil, Gas, Energy & Utilities

TekSummit – Hosted by GAO RFID Inc.

  • BLE & RFID and Their Roles in IoT & M2M
  • BLE & RFID for Industry 4.0 & 5.0
  • BLE & RFID for Intelligent Construction
  • BLE & RFID for Smart Healthcare
  • BLE & RFID for Smart Farming
  • BLE & RFID for Smart Cities
  • BLE & RFID for Intelligent Transportation & Automotive
  • BLE & RFID for Smart Utilities, Energy, Oil & Gas

TekSummit – IoT & M2M Research & Development

Hosted by GAO Research Inc.
Topics

Research & Development on Emerging Technologies and Paradigms in IoT & M2M

  • Quantum Computing Integration with IoT for Ultra-Fast Data Processing
  • Edge AI and Federated Learning in IoT Networks
  • Tactile Internet: Real-Time IoT Systems with Low-Latency Communication
  • Digital Twin Frameworks for IoT Applications
  • Neuromorphic Computing for IoT Sensor Networks
  • IoT-Enabled Cyber-Physical Systems (CPS) for Industry 5.0
  • Quantum Key Distribution (QKD) for IoT Security.
  • Evolution of Tactile Internet in Remote Surgery and Autonomous Vehicles.
  • Bio-IoT Systems for Real-Time Biometric Authentication.
  • Role of DNA Storage in IoT Data Preservation.
  • IoT in Heterogeneous 6G Environments.
  • AI-Driven Context Awareness in IoT Devices.
  • Hybrid Digital Twin Models Integrating Edge and Cloud Analytics.

Research & Development Topics on IoT & M2M Architectures and Protocols

  • Next-Generation IoT Architectures for Massive Device Scalability
  • Protocol Innovations for Ultra-Low Power IoT Devices
  • Lightweight and Adaptive Communication Protocols for Resource-Constrained IoT
  • Interoperability Standards and Protocol Stacks in IoT Ecosystems
  • Cognitive IoT Architectures for Smart Resource Management
  • Fog Computing vs. Edge Computing in IoT Architectures.
  • Interoperability Layers for Cross-Vendor IoT Platforms.
  • Microservices Architectures for IoT-Oriented Applications.
  • Device-to-Device (D2D) Communication Protocols in IoT.
  • Decentralized IoT Protocol Design for Ad-Hoc Networks.
  • Middleware Development for Seamless IoT Interconnectivity.

Research & Development Topics on Advanced IoT & M2M Hardware Development

  • Nanotechnology in IoT Sensors for High Precision and Sensitivity
  • MEMS-Based IoT Devices for Micro-Scale Monitoring
  • Ultra-Low Power Chipsets for IoT Applications
  • Advanced Antenna Designs for Long-Range IoT Connectivity
  • Energy Harvesting Technologies for Self-Sustained IoT Devices
  • Advanced Materials for Flexible IoT Sensors.
  • Ultra-Wideband (UWB) Chips for IoT Positioning and Tracking.
  • Battery-Free IoT Devices Using Ambient RF Energy.
  • High-Performance FPGA-Based IoT Gateways.
  • Scalable Manufacturing of Nano-Sensors for IoT Applications.
  • Advanced Packaging Techniques for IoT Miniaturization.

Research & Development Topics on Connectivity and Communication

  • 5G and Beyond: Enabling Massive IoT Connectivity
  • Low Earth Orbit (LEO) Satellites for Global IoT Coverage
  • LPWAN Technologies: LoRaWAN, Sigfox, and NB-IoT in Smart Applications
  • Multi-Access Edge Computing (MEC) in IoT Networks
  • Dynamic Spectrum Sharing and Cognitive Radio for IoT Communication
  • Millimeter-Wave Technology for IoT Communication in Dense Urban Areas.
  • Cross-Layer Optimization in IoT Network Protocols.
  • UAV-Assisted IoT Networks for Remote Connectivity.
  • Adaptive Beamforming in IoT Antenna Systems.
  • Dynamic Frequency Sharing for IoT Coexistence in Crowded Spectrums.
  • Role of Wi-Fi HaLow (802.11ah) in IoT Networks.

Research & Development Topics on IoT & M2M Data Management and Analytics

  • Real-Time Big Data Analytics in IoT Systems
  • Distributed Ledger Technology (DLT) for IoT Data Integrity
  • Data Lakes and Data Fabric for IoT Data Fusion
  • Predictive Maintenance Using IoT-Driven AI Models
  • Advanced Machine Learning Models for IoT Data Streams
  • Event-Driven Architectures in IoT Data Processing.
  • Adaptive Machine Learning Algorithms for IoT Data Streams.
  • Multimodal Data Fusion for Enhanced IoT Insights.
  • Managing Streaming IoT Data with Apache Kafka.
  • Real-Time Event Correlation for IoT Anomaly Detection.
  • IoT Knowledge Graphs for Contextual Data Understanding.

Research & Development Topics on IoT & M2M Security and Privacy

    • Zero Trust Architectures in IoT Networks
    • Blockchain-Based Security Frameworks for IoT
    • Post-Quantum Cryptography in IoT Ecosystems
    • Privacy-Preserving Machine Learning for IoT Data
    • Intrusion Detection and Anomaly Detection Systems in IoT
    • AI-Powered Threat Hunting in IoT Ecosystems.
    • Secure Boot Processes for IoT Devices.
    • Digital Watermarking Techniques for IoT Data.
    • Advanced Key Management Systems for IoT Networks.
    • Multi-Factor Authentication Systems Tailored for IoT Devices.
    • Role of Homomorphic Encryption in IoT Privacy Preservation.

Research & Development Topics on IoT & M2M Applications in Specific Domains

Smart Cities

  • IoT-Based Traffic Management and Vehicle Telematics.
  • Advanced Waste Management Using IoT Sensors.

Industrial IoT (IIoT)

  • Digital Twin Integration in Predictive Maintenance.
  • Process Control Optimization Using IIoT Sensors.

Precision Agriculture

  • IoT for Autonomous Agricultural Machinery.
  • Soil Nutrient Mapping Using IoT Sensor Networks.

IoT in Healthcare

  • Remote Patient Monitoring Using Implantable IoT Devices.
  • Predictive Analytics in IoT-Based Clinical Workflows.

Environmental Monitoring

  • IoT for Early Detection of Natural Disasters.
  • Smart Irrigation Systems for Water Resource Optimization.

Research & Development Topics on IoT & M2M Systems Optimization

  • Software-Defined Networking (SDN) in IoT Architectures
  • Dynamic Resource Allocation in IoT Ecosystems
  • Adaptive QoS Management for IoT Devices
  • Optimizing Energy Efficiency in IoT Deployments
  • Network Slicing for IoT Applications in Multi-Tenant Environments
  • Traffic Engineering Techniques for IoT Networks.
  • AI-Based Load Balancing in IoT Ecosystems.
  • Cross-Platform Performance Monitoring for IoT.
  • Optimization of Multi-Hop Communication in IoT Networks.
  • Reducing Latency in Resource-Constrained IoT Devices.
  • Energy-Efficient Routing Algorithms for IoT Systems.

Regulatory and Ethical Considerations

  • International Standards and Regulations for IoT & M2M
  • Ethical AI in IoT Decision-Making Systems
  • Policy Frameworks for IoT Data Ownership and Governance
  • Cross-Border Data Flow Challenges in IoT Deployments
  • Human-Centric IoT Development for Sustainable Systems
  • Compliance Frameworks for GDPR and CCPA in IoT.
  • Ethical Guidelines for IoT Data Monetization.
  • AI Governance in IoT Decision-Making Systems.
  • IoT Standards in Smart Transportation and Mobility.
  • Policy Design for Shared IoT Network Infrastructures.
  • IoT Ecosystem Accountability and Transparency Mechanisms.

Research & Development Topics on Tools and Platforms for IoT & M2M Development

  • Advanced IoT SDKs and Frameworks
  • Simulation Tools for IoT System Validation
  • Scalable IoT Platforms for Enterprise Applications
  • IoT Testbeds for Real-World Prototyping
  • Cloud-Native Architectures for IoT Deployment
  • Comparative Analysis of IoT SDKs: AWS IoT Core vs. Google IoT.
  • Role of Kubernetes in Scaling IoT Applications.
  • IoT Emulators and Testbeds for Large-Scale Deployment Testing.
  • Advanced IoT IDEs for Streamlined Development.
  • DevSecOps Practices in IoT Software Development Life Cycle.
  • Open-Source IoT Platforms for Rapid Prototyping.

Research & Development Topics on IIoT Platforms

Research Topics Across IIoT Platforms

  • Evaluating scalability, interoperability, and performance metrics across major IIoT platforms.
  • A study of approaches and challenges in edge computing integration with cloud services.
  • Examining platform-level vulnerabilities and solutions in industrial environments.
  • A comparative study of digital twin capabilities and their industrial applications.
  • Assessing the deployment of AI-driven insights for predictive maintenance and optimization.

IIoT Platform-Specific Research Topics

  • Scalability in AWS IoT Deployments: Exploring strategies for managing large-scale industrial IoT implementations.
  • Integration of AWS IoT Greengrass with On-Premises Systems: Challenges and opportunities for hybrid deployments.
  • Real-Time Analytics in AWS IoT Core: Effectiveness in enabling actionable insights for industrial operations.
  • Machine Learning Applications with AWS IoT: Leveraging Amazon SageMaker for predictive maintenance and anomaly detection.
  • Case Studies in AWS IoT Adoption: Success stories and lessons from large-scale implementations in manufacturing and energy.
  • Digital Twins and Industry 4.0: Assessing the role of Azure Digital Twins in industrial automation.
  • Hybrid Cloud Strategies with Azure IoT Edge: Balancing local processing with cloud-based analytics.
  • Interoperability of Azure IoT with Legacy Systems: Addressing challenges in integrating outdated infrastructure.
  • Role of IoT Hub in Secure Device Management: Techniques for securing endpoints in Azure IoT ecosystems.
  • Use Cases for Azure IoT in Agriculture and Smart Cities: Evaluating industry-specific deployments.
  • AI-Driven Insights in Siemens MindSphere: Evaluating effectiveness in manufacturing and energy sectors.
  • Plug-and-Play Connectivity Challenges in Industrial Environments: Analysis of MindSphere’s integration approach.
  • Digital Ecosystem Development with MindSphere: Enabling collaboration between industrial and technology partners.
  • Tailored Solutions for Energy Sector Using MindSphere: Addressing the unique challenges of renewable energy integration.
  • Real-Time Monitoring Applications in Manufacturing: Case studies from Siemens MindSphere deployments.
  • Augmented Reality (AR) Integration in IIoT: Analyzing PTC ThingWorx’s AR capabilities for industrial training and visualization.
  • Model-Driven Rapid Application Development: Evaluating ThingWorx’s role in accelerating IIoT project timelines.
  • Interoperability with Industrial Protocols: Challenges and opportunities in multi-protocol environments.
  • Digital Twins in ThingWorx Ecosystems: Enhancing operational efficiency through advanced simulations.
  • Predictive Analytics in Heavy Industry: A focus on ThingWorx’s machine learning integration.
  • Optimizing Heavy Industries with Predix: Applications in aviation, energy, and transportation.
  • Asset Performance Management (APM) Capabilities in Predix: Techniques for extending equipment lifespans.
  • Digital Transformation in Energy with Predix: Enabling smarter grids and renewable energy management.
  • Real-Time Data Analytics for Transportation: Improving efficiency in railways and aviation.
  • Case Studies of GE Predix Deployments: Lessons learned from industry-specific implementations.
  • AI-Driven Predictive Maintenance: Evaluating the Maximo suite’s capabilities for reducing downtime.
  • Integration of Maximo with Enterprise Asset Management Systems: Addressing complexities in legacy environments.
  • Advanced Asset Monitoring Techniques with Maximo: Insights from heavy industry applications.
  • AI and IoT Synergy in the Maximo Ecosystem: Enhancing decision-making in real-time.
  • Sustainability in Industrial Operations: Maximo’s role in promoting energy efficiency.
  • AI and Edge Computing in Lumada: Bridging the gap between real-time data processing and analytics.
  • Modular Solutions for Industrial Automation: Analyzing flexibility in Lumada deployments.
  • Energy Efficiency and Sustainability with Lumada: Case studies in green industrial practices.
  • IoT Analytics in Smart Manufacturing: Exploring Lumada’s role in enabling Industry 4.0.
  • Integration with Cloud and On-Premises Systems: Overcoming challenges in hybrid Lumada deployments.
  • Supply Chain Optimization with SAP IoT: Enabling visibility and resilience in industrial supply chains.
  • Seamless Integration with ERP Systems: Examining SAP IoT’s capabilities in manufacturing environments.
  • Real-Time Analytics for Production Optimization: Evaluating SAP IoT’s role in process industries.
  • IoT-Enabled Quality Control in Consumer Goods: Applications in food and beverage production.
  • Data-Driven Insights for Business Operations: Leveraging SAP IoT for decision support systems.
  • IIoT-Driven Energy Management: Analyzing EcoStruxure’s impact on industrial energy consumption.
  • Real-Time Control in Smart Factories: Applications of EcoStruxure in discrete manufacturing.
  • Sustainability Initiatives Enabled by EcoStruxure: Enhancing energy efficiency across sectors.
  • IoT Solutions for Smart Buildings: Case studies of EcoStruxure implementations.
  • Automation in Critical Infrastructure: Examining EcoStruxure’s role in water and power sectors.
  • Real-Time Factory Floor Visibility: Evaluating FactoryTalk’s capabilities for improving productivity.
  • Edge Analytics in Process Manufacturing: Applications of FactoryTalk in refining and chemical industries.
  • Digital Transformation in Automotive Production: Lessons from FactoryTalk deployments.
  • Predictive Maintenance Tools in Discrete Manufacturing: Case studies of FactoryTalk implementations.
  • Role in Industrial IoT Ecosystems: Enhancing interoperability across connected devices.
  • IoT Analytics in Connected Mobility: Examining Bosch’s role in the automotive sector.
  • Real-Time Device Management Solutions: Analyzing the scalability of Bosch IoT Suite.
  • Smart Agriculture Applications: Using IoT for sustainable farming practices.
  • Logistics and Supply Chain Enhancements: Insights from Bosch IoT Suite’s industrial applications.
  • Developer Ecosystem for Industrial IoT: Promoting innovation through open platforms.
  • Operational Intelligence in Critical Infrastructure: Applications in energy and aerospace.
  • Energy Efficiency in Industrial Buildings: Analyzing Honeywell Forge’s sustainability impact.
  • Enterprise Analytics for Performance Monitoring: Exploring Honeywell Forge’s data-driven insights.
  • IoT Solutions for Urban Infrastructure: Case studies in smart city deployments.
  • Automation in Commercial Aviation: Honeywell Forge’s role in flight operations optimization.

Research & Development Topics on Combining IoT with Drones Effectively

  • IoT Protocol Optimization for Drone Networks: Investigate the adaptation of protocols like MQTT, CoAP, and LPWAN for drone-based IoT systems.
  • 5G and Beyond for Drone IoT Connectivity: Explore the role of advanced cellular networks in enhancing IoT-enabled drone communication.
  • Swarm Intelligence with IoT Integration: Study IoT architectures for enabling autonomous drone swarms using real-time data sharing and decision-making.
  • Energy Harvesting Solutions for IoT Drones: Research solar, wind, and RF-based energy harvesting for extending drone operational time.
  • IoT-Driven Power Optimization in Drone Systems: Develop IoT frameworks for real-time power consumption monitoring and optimization in drones.
  • Multi-Sensor Fusion for IoT Drones: Investigate techniques for fusing data from IoT sensors on drones for enhanced environmental monitoring and analysis.
  • IoT-Based Real-Time Calibration of Drone Sensors: Study adaptive calibration methods to ensure consistent sensor accuracy.
  • IoT-Assisted Navigation for Drones: Explore IoT’s role in enhancing GPS, LiDAR, and computer vision-based navigation systems.
  • Edge Computing for IoT Drone Autonomy: Research edge AI solutions for enabling drones to make decisions locally based on IoT sensor data.
  • IoT-Driven Drone Analytics Platforms: Develop systems for real-time data analysis and visualization from drone IoT sensors.
  • IoT and Drone Integration for Disaster Management: Study how IoT-enabled drones can provide real-time situational awareness during emergencies.
  • IoT Drones for Smart Agriculture: Explore applications such as precision irrigation, pest monitoring, and crop health analysis using IoT-equipped drones.
  • IoT-Based Inspection Systems with Drones: Research drone applications in inspecting infrastructure like bridges, pipelines, and power lines using IoT data.
  • IoT Drones for Air Quality Monitoring: Investigate the deployment of IoT-enabled drones for tracking pollutants and greenhouse gases.
  • IoT and Drones for Wildlife Tracking: Study systems for monitoring animal populations and migration patterns using IoT data and drones.
  • IoT-Enhanced Drone Surveillance Networks: Research how IoT can enable efficient, large-scale drone surveillance with real-time data sharing.
  • IoT-Driven Threat Detection with Drones: Explore integration of IoT sensors for early detection of potential threats in sensitive areas.
  • IoT-Driven Drone Delivery Systems: Investigate the use of IoT technologies for optimizing drone-based package delivery routes and tracking.
  • IoT Drones for Inventory Management: Study the deployment of drones for automated inventory counting in warehouses.
  • IoT Drones for Traffic Monitoring: Explore IoT and drones for real-time traffic pattern analysis and congestion management.
  • IoT-Driven Airspace Management for Urban Drones: Research frameworks for safe and efficient drone operations in urban environments.
  • IoT Drones for Post-Disaster Assessment: Study how IoT-enabled drones can assist in assessing damage and locating survivors after disasters.
  • IoT and Drone Integration for Rapid Relief Deployment: Research systems for delivering aid supplies efficiently using IoT drones.
  • IoT-Driven Medical Supply Drones: Explore how IoT can enable drones to deliver medical supplies and monitor patient health in remote areas.
  • IoT and Drones for Epidemic Monitoring: Study drone-based IoT systems for tracking disease outbreaks and monitoring quarantined zones.
  • Cybersecurity in IoT-Drone Systems: Investigate vulnerabilities and solutions for securing IoT-enabled drone communication and data.
  • Standardization and Interoperability for IoT Drones: Study the need for global standards and protocols for seamless IoT-drone integration.
  • IoT-Driven D2D Collaboration: Research frameworks for drones to communicate and collaborate in real-time using IoT protocols.
  • IoT Solutions for Drone-to-Ground Data Relays: Study the role of IoT in enhancing the efficiency and reliability of ground station communications.
  • AI-Driven Decision Making for IoT Drones: Explore AI algorithms that use IoT data for autonomous drone decision-making.
  • Machine Learning for Predictive Maintenance in IoT Drones: Investigate predictive maintenance techniques for drone components based on IoT sensor data.

Research & Development Topics on IoT for Testing

  • IoT-Based Systems for Air Quality Assessment: Development of real-time IoT networks to monitor pollutants, greenhouse gases, and particulate matter.
  • IoT Sensors for Climate Change Analysis: Applications of IoT in tracking and modeling changes in temperature, humidity, and atmospheric pressure.
  • IoT-Driven Biodiversity Monitoring: Use of IoT devices to assess and maintain ecological balance by tracking species populations and environmental conditions.
  • IoT Solutions for Hazardous Chemical Leak Detection: Integration of IoT sensors in industrial settings for early detection and containment of chemical spills.
  • IoT-Based Smart Labs for Chemical Analysis: Developing IoT-enabled laboratories for remote monitoring and analysis of chemical reactions.
  • IoT Applications in Soil Chemistry Testing: Use of IoT devices to measure pH, nutrient levels, and contamination in soil.
  • IoT for Real-Time Water Quality Monitoring: Deployment of IoT devices to track pH, turbidity, dissolved oxygen, and contaminants in water bodies.
  • Smart IoT Networks for Detecting Heavy Metals: Research on IoT-enabled sensors to detect lead, mercury, and arsenic in drinking water.
  • IoT and Cloud Integration for Aquatic Ecosystem Health: Development of systems to monitor and analyze water quality trends using IoT and cloud platforms.
  • IoT for Nuclear Radiation Monitoring: Design of IoT systems for detecting and measuring radiation levels in nuclear plants and surrounding areas.
  • IoT-Driven Dosimetry in Healthcare and Industry: Development of wearable IoT devices to track radiation exposure for medical personnel and industrial workers.
  • IoT and AI for Radiation Mapping: Combining IoT sensors and AI algorithms to create detailed radiation maps for disaster response.
  • IoT for Real-Time Bridge Safety Analysis: Research on IoT-enabled sensors for detecting cracks, stress, and corrosion in bridge structures.
  • IoT in Earthquake-Resistant Building Designs: Development of IoT systems to monitor structural integrity and predict seismic impacts.
  • IoT Solutions for Aging Infrastructure Maintenance: Applications of IoT in assessing the condition of aging buildings, pipelines, and roadways.
  • IoT-Based Systems for Industrial Effluent Monitoring: Use of IoT devices to monitor and control pollutants in industrial discharge.
  • Smart Farming with IoT for Soil and Water Analysis: Development of IoT solutions to test and optimize soil and irrigation water quality in agriculture.
  • IoT for Urban Pollution Management: Integrated systems to monitor air and water pollution simultaneously in smart cities.
  • IoT for Toxic Gas Detection in Disaster Zones: Development of portable IoT devices for monitoring and reporting hazardous gas levels post-disaster.
  • IoT Systems for Radiation Management in Nuclear Incidents: Applications of IoT for real-time radiation detection and safety management during nuclear emergencies.
  • IoT Networks for Flood Water Quality Analysis: Research on IoT sensors for testing water contamination during flood events.
  • Big Data Analysis of IoT-Generated Environmental Data: Leveraging IoT data for predictive insights into environmental trends.
  • AI-Powered IoT for Chemical Process Optimization: Use of machine learning to improve IoT-based monitoring in chemical testing facilities.
  • IoT-Enabled Digital Twins for Structural Analysis: Development of digital replicas of infrastructure for testing and monitoring using IoT sensor data.
  • IoT for Testing in Remote or Hostile Environments: Deploying IoT systems in remote regions for environmental and structural testing.
  • IoT in Monitoring of Offshore Structures: Applications of IoT for testing the integrity of oil rigs, marine vessels, and underwater pipelines.
  • IoT-Enabled Autonomous Testing Drones: Combining IoT with drones for data collection in inaccessible or dangerous areas.
  • Wearable IoT for Monitoring Toxic Exposure: Research on personal IoT devices to monitor environmental hazards affecting workers’ health.
  • IoT-Integrated Early Warning Systems for Radiation Hazards: Development of community-based IoT networks for radiation alerts.
  • IoT Applications in Fire Safety Testing: Use of IoT to analyze and predict fire risks in buildings and industrial setups.
  • Development of IoT Standards for Environmental Monitoring: Research on global standards for IoT sensors and networks in environmental applications.
  • Interoperability Challenges in Multi-Parameter IoT Testing Systems: Addressing the integration of IoT devices for testing diverse parameters like water, air, and radiation.

Future Directions in IoT R&D

  • Autonomous IoT Systems with Self-Healing Capabilities
  • Collaborative Swarm Intelligence in IoT Devices
  • Quantum Internet Integration for IoT Devices
  • Bio-IoT Systems for Healthcare and Biometrics
  • AI-Driven Automation in IoT Software Development Life Cycle (SDLC)
  • Integration of IoT with Self-Organizing Networks (SON).
  • IoT in Space: Sensor Networks for Satellite Operations.
  • Convergence of IoT and Synthetic Biology.
  • Advanced Imaging Sensors for IoT in Medical Applications.
  • Role of IoT in Human Augmentation Systems.
  • Evolution of Collaborative IoT Systems with Swarm Intelligence.
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