London’s air pollution leaves much to be desired. However, current urban air quality measurement systems rely on sensors that are often positioned well above street level, so they do not accurately capture the exposure that pedestrians face.

So why not put the sensors on the same level as the humans instead? The Internet Of Things Academy has developed BuggyAir, a mobile system for air quality monitoring by attaching IoT devices to children’s buggies in major cities across the UK.

This is just one example of how sensors, used in tandem with location analytics, can help boost quality of life and make cities smart. We share three ways how IoT networks are making our lives more comfortable and safe.

1. Crowdsourcing air quality monitoring

With sensors right on children’s pushchairs, BuggyAir measures air where it is actually breathed in by pedestrians, and on the actual routes that they typically follow. What’s more, unlike urban air quality systems, buggies are not static, and can provide a more accurate picture of air quality in the immediate vicinity.

The sensor detects three common types of harmful pollutants in the air, and feeds these data back to a central system. The system then creates a dynamic air quality map by automatically uploading anonymised air quality data from pushchair sensors around the city, and aggregating the data in a location-based analytics platform.

This way, city authorities are able to make better informed planning decisions based on a more realistic picture of air pollution. Meanwhile, citizens are able to make informed choices about which routes to walk, and avoid pollution hotspots.

2. More efficient refuse collection

A number of UK cities have successfully completed trials on sensor-equipped bins which provide data on the waste they contain. These smart bins have ultrasonic beams to measure the level of waste in the bin, a gas sensor to identify the age and type of the waste, and GPS to give its location. This information is transmitted back to a central server via a wireless network, so the system can predict which bins will need emptying when.

By combining bin locations with street maps and real-time traffic information, the system is able to plan the shortest possible routes for collection trucks, so that they only visit the sites where a collection is needed. This results in around 30% fewer bin collections.

3. Smart homes and geofences

Owners of smart homes could use a geospatial app to erect a geofence for greater convenience. If they decide to return home early one day, the heating system is not aware, so the temperature could be too cold or too hot for him or her when they get home. With the app, their smartphone will trigger the geofence, so that the heating system will be alerted to change the temperature in time for their arrival.

Let’s take it a step further: If a thousand people changed their plans, the energy suppliers could be given advanced warning of an expected surge in usage. Power generation supplies can be adjusted to meet changing demand.

We live in a world where it is now possible for a network of physical objects – vehicles, buildings, infrastructure, equipment of all shapes and types – to collect and exchange data, and to work together. Here, telecommunications providers have an immense opportunity to provide the IoT platforms and infrastructure that form the backbone of these networks.

For more details on these case studies, download the eBook by filling out the form below.

Join us to explore smart cities, urban design, and location analytics at the Esri Singapore User Conference on 27 September in Singapore.

Image from Friends of the Earth Scotland on Flickr – CC BY 2.0