The Increasing Significance of IoT in GIS

Applied Tech Review | Wednesday, September 15, 2021

Due to the critical nature of the location in IoT data, many organizations and businesses have discovered that a contemporary GIS fed by real-time data may be a useful operational tool.

FREMONT, CA: The Internet of Things (IoT) is a global network comprising billions of sensors. Because they are all connected, information may be sent between them.

The large amount of real-time sensor data generated by the Internet of Things comes from physical devices such as smartphones, computers, homes, and automobiles.

Geographic location is the link between IoT and GIS. Most gadgets integrate their physical location with a GPS receiver, providing real-time sensor data and positioning.

The geospatial sector has embraced this geographic context provided by the IoT.

Real-Time Location Positioning: IoT is a networked world of moving sensors, fixed meters, and social media feeds. For instance, the following are some types of sensors that contribute to the IoT:

  • Vehicles that are connected
  • Feeds for soil moisture monitoring
  • Intelligent electricity meters

These stream layers are available through cloud service providers like Azure, Amazon, or Cisco. Following that, people connect to these sources to obtain real-time data and locations.

In GIS, objects such as transit bus sensors are immediately pushed to the map with their most recent location and information. However, we can make connections beyond this.

Sensors in intelligent parking lots, traffic cameras, and geofencing are all available.

Big Data Analytics: Big data analytics analyzes massive amounts of data to identify patterns on a larger scale.

This data could have been gathered over an extended time and could include millions of point locations.

In general, big data analytics scales data, making it more manageable.

This enables the building of visualizations and analyzes on the fly in GIS. Additionally, one may create time animations and visualize spatiotemporal patterns.

Spatial Analytics in Real-Time: Real-time analytics is advantageous for interpreting and acting on real-time observational data.

If a bus always takes the same route, any deviation from that course could pose a safety issue.

In this instance, real-time spatial analysis can be performed. If the bus deviates from its allowed route, it can generate an event if the deviation exceeds a certain threshold.

For instance, one can send an email to a transit manager automatically. They can then take action to conduct additional investigations.

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