Bridging the Gap: IoT Data with GIS and AI for Enhanced Mapping and Analysis - Underwater Inspection

While IoT devices such as sensors and UUVs can collect a wide range of data underwater, the data collected by these devices lacks context and can be difficult to interpret without a spatial framework. This is where GIS (Geographic Information System) comes in. GIS can provide a spatial context to the data collected by IoT devices, enabling users to visualize and analyze the data in a more meaningful way. such as, GIS can create maps that show the location of underwater structures, the depth of the water, and the location of potential hazards such as rocks or shipwrecks. This information can then be used to plan and execute underwater inspections more effectively.

GIS can integrate data from multiple sources, including IoT devices, to provide a more comprehensive view of the underwater environment. For example, GIS can integrate data from UUVs with other data such as bathymetry data, weather data, and satellite imagery to provide a complete picture of the underwater environment. This integration of data provides valuable insights into the underwater environment, enabling a more informed decision-making process.As we know,?GIS is a tool for gathering, storing, analysing, and displaying geographically referenced data about the Earth's surface. By presenting complicated data relationships and patterns on a map, GIS enables us to observe and comprehend them. In contrast, IoT devices produce massive amounts of real-time data from sensors that measure things like temperature, humidity, and air quality. Using these two technologies together allows us to display and analyze IoT data in a spatial context, which can lead to fresh perspectives and better decision-making.??

Creating bathymetry mapping and data through GIS, AI, and IoT going through following stages:

1. Collecting Data: The first step is to collect bathymetry data using IoT devices such as unmanned underwater vehicles equipped with sonar sensors. The UUVs can be programmed to follow specific routes and collect data at regular intervals, producing a detailed map of the underwater environment.

2. Pre-processing Data: The data collected by the vehicle may contain noise, anomalies, or missing values. Therefore, it is necessary to preprocess the data using techniques such as filtering, interpolation, and smoothing. This ensures that the data is accurate and reliable for further analysis.

3. Mapping Data: Once the data is preprocessed, it can be mapped using GIS software such as ArcGIS or QGIS. GIS allows us to visualize and analyze bathymetry data in a spatial context, creating 2D or 3D maps of the underwater environment. This mapping process can also identify underwater features such as canyons, ridges, and seamounts.

4. Analyzing Data: After mapping the data, AI algorithms can be used to analyze the bathymetry data in real-time and provide predictive insights. For example, AI can be used to identify the presence of underwater structures, such as oil rigs or shipwrecks, based on bathymetry data. AI can also be used to predict the behaviour of underwater currents and tides.

5. Visualization: The final step is to visualize and communicate the results of the analysis. The maps and insights generated by the analysis can be visualized using GIS software, creating interactive and informative maps that can be shared with stakeholders.?

6. Data Integration: To provide a complete picture of the undersea environment, GIS can combine data from various sources, including IoT devices. For instance, to provide a complete view of the underwater environment, data from the sensors on vehicle can be merged with additional data like bathymetry, weather, and satellite photography.

7. Real-time data visualisation allows users to observe and react to changes in the undersea environment in real-time. GIS can display real-time data from IoT devices. Applications like underwater structure inspection, where real-time monitoring is essential to ensure safety and avoid structural damage, make good use of this functionality.

3D visualisation: GIS can be used to create 3D models of the underwater environment for visualisation and scientific research. The capacity of GIS software to create 3D maritime environment visualisations enables a more thorough and engaging interpretation of the data gathered by IoT sensors. Applications like marine exploration, where it is essential to have a complete grasp of the underwater environment, benefit greatly from this capability. Through the use of point symbols, lines, and polygons, spatial data, such as the placement of IoT devices, water depth, and underwater structures, can be visualised using GIS software.

Enhancement images: To improve the quality of images obtained during underwater inspections, GIS and remote sensing techniques can be used to enhance them. Spatial analysis techniques such as filtering, image enhancement, and feature extraction can be applied to reduce noise, improve contrast and sharpness, and identify specific features like underwater structures and marine life.

However, The Ocean Floor Mapping Project is one instance of how GIS and IoT are used to analyse underwater bathymetry data. High-resolution bathymetry data is being gathered for this research using UUVs fitted with sonar sensors, which is being overseen by the National Oceanic and Atmospheric Administration (NOAA). The ocean floor is then meticulously mapped utilising GIS processing and mapping of this data. This data is utilised for a variety of things, including locating potential sites for offshore wind farms and locating potential habitats for threatened and endangered species.

Satellite imagery can be used to measure water clarity by capturing data on the reflectance of light from the water's surface. Water clarity is crucial for aquatic ecosystem health and potential hazard identification. High water clarity allows for easy identification of underwater structures and marine life, while low clarity reduces visibility. Changes in clarity indicate the presence of sedimentation, pollutants, or changes in phytoplankton concentration. These changes can also indicate potential hazards like submerged rocks or shipwrecks. With satellite imagery, GIS provides valuable insights into water clarity for decision-making related to underwater inspections, marine transportation, and environmental management.

GIS offers a geographical framework for analysing and understanding this data, whereas IoT devices can collect data underwater. GIS can help users plan and carry out underwater inspections more successfully and make better decisions by giving them a complete picture of the undersea environment..