The Spatial Internet of Things

| |


The development of small sensors that provide a variety of spatial data in real-time is beginning to revolutionizing how we live and conduct business. We are likely only at the beginning of this development phase, although it perhaps is beginning to mature, as shared in a recent geospatial podcast with Geoffrey Mair from SensorUp.

What is IoT?

The Internet of Things (IoT) is the use of a variety of sensors and devices with unique identifiers that can send information about objects or people over a network with that data not requiring human-to-human or human-machine interaction. Spatial IoT provides unique location and time information along with other data about items monitored. What makes IoT and spatial IoT useful is the low cost nature of sensors and that these sensors can be used in real-time. By connecting sensors in homes, business, and other locations, then it is possible for companies, researchers, and others to have the ability to track a variety of information in real-time and apply different spatial operations.[1]

Why is Location Data Important

For IoT, location data are critical as information is tracked in space and time. Spatial data are the common thread for data and information is keyed or tagged based on space and time. The SensorThings Standard has been created by the Open Geospatial Consortium (OGC) as a open standard for IoT devices that enables interoperability between devices and sharing of data. Using this standard, devices can take disparate data, such as different a clustered network of sensors, and aggregate information in a standard format while tagging information such as coordinates and timestamp information with the root or focused observation for given devices provided. The standard makes it possible to apply different analyses in a variety of domains, including in public safety, transportation, household consumer goods, military, and other areas. It is also possible for different organizations to share devices and data using this standard, which facilitates data integration.

Real-time Mapping

With the tracking of space and time data, it is possible to create real-time maps that apply a variety of analyses including artificial intelligence (AI) and spatial operations that can assist in decisions in different areas. Data that are derived from sensors but are not part of the primary data collection are second-order metrics that can aid a workflow engine that builds rules or uses AI in programmed responses. For instance, sensors in buildings and individuals that are collected enable responses to real-time events and coordinating these events with first responders in public safety situations. In other cases, body sensors could be connected to a smart-hub and used in simple android phones, where such data can be used to track police, fire, and others during an event. Such data, whether it is for individuals or buildings, can be integrated and coordinated in real-time so that the best response can be made. Automate steps could also be built into workflow software that processes and detects conditions from sensor data. Such data can be used to track waste or inefficiencies including bottlenecks in networks and re-root traffic. Historical data collected from sensors along with real-time data could be used together to optimize decisions and decision-making functions. It is possible improve location information by using multiple sensors together such as GPS and location tracking systems, including from phones, being combined together to provided weighted real-time location data.

The PurpleAir map crowdsources air quality readings from Internet of Things sensors.
The PurpleAir map crowdsources air quality readings from Internet of Things sensors.

Future Developments

Big opportunities in the future are evident in different areas, including in industrial applications where IoT could bring a type of new industrial revolution. In fact, we are starting to see this happen with smartspeaker devices such as Alexa. Such devices can track information over time and such devices can make decision for consumers. There are, of course, concerns on security with these devices, particularly if they are hacked or data are stolen, but the benefits may outweigh concerns given they can help in areas of safety and help decisions made for us. We might be now at the beginning of a more mature phase in the Gartner Hype Cycle for IoT, where broader adoption is beginning to happen as companies and researchers take advantage of the SensorThings standard. This could mean in a few years time such sensors will be ubiquitous and adoption and application of IoT devices and optimization using sensor data could be standard practice.


[1]    For more on IoT and its capabilities, see:  Khan, J.Y. and Yuce, M., 2019. Internet of Things (IoT): Systems and Application. Jenny Stanford Publishing.



Find Maps and GIS Data from Esri’s Hurricane Hub

Mapping Tropical Forest Quality from Satellite Data