WSN IOT Research Topics

By using WSN in the IoT environment, it is made easy for gathering data and transferring it through network. You can learn more and gain better knowledge on this topic WSN assisted IoT system by completely reading this research paper.

  1. Define WSN Assisted IoT

Combining Wireless Sensor Network (WSN) with the diverse Internet of Things (IoT) ecosystem of different applications and devices is known as the WSN assisted IoT. WSN is a sensor network which is small in size with low power consumption, used in gathering data and to transmit it. These are fitted to sensor for collecting real time data like humidity, temperature, motion, light and many; from the environment where they have been placed.

  1. What is WSN Assisted IoT?

WSN is incorporated with IoT devices to improve its function and effectiveness. The networked sensors in WSN collect data from surrounding with low power consumption. The WSN helps IoT by maintaining a local and precise gathering of data, decision making and real-time monitoring. It is used in several industries like industrial automation, healthcare, agriculture and environmental monitoring. Combining both WSN and IoT helps in improving collection of data, analysis and transmission of it, which produces a smart and responsive system.

  1. Where WSN Assisted IoT is used?

In this section we are going to discuss about the uses of this WSN assisted IoT system. This is used in many industries for various applications for its great capacity of data gathering, decision making and real-time monitoring.

  1. Why WSN Assisted IoT is proposed? Previous Technology Issues

Moving on to the next section, here we are going to discuss about the reason for the proposal of this technology and the challenges faced by this WSN assisted IoT technology. This technology was proposed to overcome the drawbacks faced by earlier technologies in energy consumption to increase the performance. Some of the issues regarding it are listed here:

Optimal Cluster Formation and Balancing Energy Consumption: The clusters in WSN have CH which will gather data from all the members of cluster and transmit it to a sink or base station. Identifying formation for cluster is a difficult task because lifetime of the network should be very long and the energy usage by every node should be evenly spread. The balanced use of energy increases the system performance, network longevity and decreases node failure.

Efficient and Reliable CH Selection: This system will function properly when the CH is chose properly. The CH node, need more energy than normal node because it has to manage the data transfer in cluster. To select a reliable and efficient CH algorithm, one has to consider the energy level of node, communication capabilities and distance with the sink to increase energy efficiency and stability of the network.

Reliable and Time-efficient Route Selection: The data transfer from source to sink has multiple hops in WSN. The path for network efficiency and data integrity should have less energy consumption and delay. Choosing the route selection process is a bit difficult task because the route has to be energy efficient and robust with decreasing the computational overhead and that route should also adapt according to network topology.

Minimizing Energy Consumption during Sink Relocation and Improving Data Aggregation: relocating sink is essential when sink faces some problems like working stops on original sink or when the dynamics of network changes. Maintaining energy efficiency is important while relocating sink. Relocation should result in enhanced data aggregation, data gathering and reduced useless data transfer.

  1. Algorithms / Protocols

After knowing about the technology, uses of it and the issues faced by them in the earlier stage, now we are going to learn about the algorithms used for this technology. The algorithms provided for WSN assisted IoT system to overcome the previous issues faced by it are: Tri-state Markov Chain Model (Tri-MCM), Quality Aware Assessment Model (QA2M), Multi- Objective Spider Monkey Optimization (MOsMO), Energy Equivalent Cluster Formation and Validation (E2CFV), Intelligent Triangulation Method (ITM), Angle Separated Hexagon (ASep-Hex) and Hop- to-Hop Directed Acyclic Graph (H2H-DAG).

  1. Simulation results / Parameters

The approaches which were proposed to overcome the issues faced by this method in the above section are tested using different methodologies to analyze its performance. The comparison is done by using metrics like Energy Consumption, Throughput and Number of nodes, Packet Delivery Ratio and Network lifetime.

  1. Dataset LINKS / Important URL

Here are some of the links provided for you below to gain more knowledge about WSN assisted IoT system which can be useful for you:

  1. WSN Assisted IoT Applications

In this next section we are going to discuss about the applications of WSN assisted IoT system. This technology has been employed in many industries, from which some of them are listed here: In agriculture to improve pest management, irrigation and pest management and also helpful in tracking factors like temperature, humidity, crop health and soil condition, due to which there is increase in yield and sustainability also decrease in resource waste. It can also be applied in monitoring environmental conditions such as water and air quality or pollution level, this will help control the ecological changes and pollution. This system can also be employed in monitoring power distribution, controlling issues in power grid and identifying power distribution.

  1. Topology

Topology generally refers to the architecture of a network. Some of the commonly used topology for this study is mentioned here: “E2CFV and FuP” will create hexagonal WSN, “Tri-MCM” for inter-cluster routing. “ITM and MOsMO” is used for increasing candidate positions.

  1. Environment

This system works or functions better in an “energy-efficient hexagonal WSN”, along with routing, advanced clustering and in effective IoT monitoring environment.

  1. Simulation Tools

Here we provide some simulation software for previous works, which is established with the usage of NS 3 tool with version 3.36 or above version, to enhance the performance of WSN assisted IoT devices.

  1. Results

After going through this research based on Anomaly detection in WSN assisted IoT system which provide lot of information for you, so utilize this to clarify the doubts you have about its technology, applications of this technology, and different topologies of it, algorithms followed by it also about the limitations and how it can be overcome.

WSN IOT Research Ideas

  1. Performance Analysis of Clustering Protocols for WSN Assisted IoT Network
  2. Low-Power Heterogeneous Networking Method Based on NB-IoT and WSN
  3. AD-Hoc Routing Protocols in WSN-Wi-Fi based IoT in Smart Home
  4. Several Energy-Efficient Routing Protocols, Design-based Routing Problems and Challenges in IoT-Based WSN: A Review
  5. Performance Evaluation of IoT-enabled WSN system with and Without DDoS Attack
  6. Intensive Review on Hybrid Combination of WSN and IoT and its Impact
  7. A Real-Time Link Quality Estimation Method for IEEE 802.15.4 Based Wireless Sensor Network and IoT Devices
  8. Hybrid Intelligent Fusion-Based Perspectives for WSN-IOT
  9. Reduction of Energy Consumption and Increasing Network Lifetime by Ubiquitous Computing Method for WSN in IoT
  10. Estimation of Optimum Route Calculation via Multi Objective Optimization Technique for IoT Enabled WSN
  11. Gradient Enhanced Regressive Multivariate Artificial Fish Swarm Optimized Data Collection for IoT-Enabled WSN in Smart Environments
  12. Energy-Efficient Stable Election Protocol for IoT-Based Healthcare Systems Using Wireless Sensor Networks
  13. A Research Survey on Security Enhancement in WSN-based IoT Applications
  14. SCPD-IT: Smart COVID-19 Patient Detection Over IoT-WSN
  15. Remote Temperature and Humidity Measurement System with the Use of IoT and WSN for Intelligent Homes and Warehouses
  16. Ecological Observing using Sensor and IoT to Protect the Global Warming in WSN
  17. RSSI-Guided Cluster Head Selection for Optimal Optimization in IoT-Enabled WSNs
  18. A Clustering and Routing Algorithm for Fast Changes of Large-Scale WSN in IoT
  19. Development of Efficient Wireless Sensor Network for IoT Applications
  20. Metascheduling Using Discrete Particle Swarm Optimization for Fault Tolerance in Time-Triggered IoT-WSN
  21. To Expand Network Lifetime by Intrusion Method for IoT based WSN
  22. A review on WSN clustering algorithms in lot based applications
  23. A Novel and Robust Sensing Technique under Cooperative Schemes of IOT Based Industrial WSN in Real Time
  24. Conception and Design of WSN Sensor Nodes Based on Machine Learning, Embedded Systems and IoT Approaches for Pollutant Detection in Aquatic Environments
  25. A Reconfigurable CMOS Stack Rectifier with 22.8-dB Dynamic Range Achieving 47.91% Peak PCE for IoT/WSN Application
  26. A review on early forest fire detection using IoT-enabled WSN
  27. Optimized Deep Learning for Congestion-Aware Continuous Target Tracking and Boundary Detection in IoT-Assisted WSN
  28. Energy-Efficient Resource Allocation and Routing Protocols for IoT-based WSN: A Review
  29. A Low-Energy System for IoT-based Wireless Sensor Networks
  30. Enhancement of Overall Network Performance by Fuzzy Based Routing Algorithm for IoT Enabled WSN
  31. Energy Management Techniques of Wireless Sensor Networks for Internet of Things Applications
  32. Optimizing Energy Efficiencies of IoT-based Wireless Sensor Network Components for Metaverse Sustainable Development using Carry Resist Adder based Booth Recoder (CRABRA)
  33. A WSN-Based, Intelligent Medical IoT Systems Integrating Computer Vision Platform
  34. Topographic-Heterogeneous Energy Based (T-HEB) Routing Protocol for Wireless Sensor and IoT Based Networks
  35. An Energy Optimization in WSN using Dragonfly Optimization Algorithm for IoT Applications
  36. Privacy-Preserving Authentication Scheme with Revocability for Multi-WSN in Industrial IoT
  37. Enhanced Hybrid Energy-Efficient Distributed Clustering Protocol for IoT-Based WSNs with Multiple Sinks
  38. Evaluation of Wireless Sensor Networks Module using IoT Approach
  39. Enhancement of Energy Efficiency using Improved Energy Efficient Routing Protocol in Wireless Sensor Networks for IoT Applications
  40. Precision Agriculture Using Internet of Things and Wireless Sensor Networks
  41. Evaluation of Hotspot Performance in IoT Enabled Wireless Sensor Network using Special Intermediate Nodes in the Network
  42. Implementation of Internet of Things in Wireless Sensor Networks for Environmental Monitoring
  43. An Energy-Efficient Hybrid Clustering Technique (EEHCT) for IoT-Based Multilevel Heterogeneous Wireless Sensor Networks
  44. Bamboo Forest Growth Optimization with Deep Learning for Intrusion Detection in IoT-Assisted Wireless Sensor Networks
  45. Improving Connectivity in Urban IoT-based Wireless Sensor Networks: A None-orthogonal Cognitive-based Power Allocation
  46. Modeling and Implementation of an Adaptive Wireless Sensor Network for Low Power IoT Applications
  47. Application Scheduling With Multiplexed Sensing of Monitoring Points in Multi-Purpose IoT Wireless Sensor Networks
  48. High-Performance and Energy-Efficient FIR Filter Architecture Using Parallel Prefix Adder-Based Triangular Common Sub-expression Elimination Algorithm for IoT Enabled Wireless Sensor Network
  49. A Review: Secure and Efficient Data Aggregation in Wireless Sensor Networks using the Internet of Things
  50. Wireless Sensor Network and Internet of Things-based Smart Irrigation System for Farming