Tag Archives: IoT

Nature Smart Cities: Visualising IoT bat monitor data with ViLo

In the past weeks I’ve been collaborating with researchers at the Intel Collaborative Research Institute (ICRI) for Urban IoT to integrate data from bat monitors on the Queen Elizabeth Olympic Park into CASA’s digital visualisation platform, ViLo. At present we are visualising the geographic location of each bat monitor with a pin that includes an image showing the locational context of each sensor and a flag indicating the total number of bat calls recorded by that sensor on the previous evening. A summary box in the user interface indicates the total number of bat monitors in the vicinity and the total number of bat calls recorded the previous evening. Animated bats are also displayed above pins to help users quickly identify which bat monitors have results from the previous evening to look at.

The data being visualised here comes from custom made ‘Echo Box’ bat monitors that have been specifically designed by ICRI researchers to detect bat calls from ambient sound. They have been created as part of a project called Nature Smart Cities which intends to develop the worlds first open source system for monitoring bats using Internet of Things (IoT) technology. IoT refers to the idea that all sorts of objects can made to communicate and share useful information via the internet. Typically IoT devices incorporate some sort of sensor that can process and transmit information about the environment and/or actuators that respond to data by effecting changes within the environment. Examples of IoT devices in a domestic setting would be Philips Hue Lighting which can be controlled remotely using a smartphone app, or Amazon’s Echo which can respond to voice commands in order to do things like cue up music from Spotify, control your Hue lighting or other IoT devices, and of course order items from Amazon. Billed as a ‘”shazam” for bats’ the ICRI are hoping to use IoT technology to show the value of similar technologies for sensing and conserving urban wildlife populations, in this case bats.

Each Echo Box sensor uses an ultrasonic microphone to record a 3 second sample of audio every 6 seconds. The audio is then processed and transformed into an image called a spectrogram. This is a bit like a fingerprint for sound, which shows the amplitude of sounds across different frequencies. Bat calls can be clearly identified due to their high frequencies. Computer algorithms then analyse the spectrogram to compare it to those of known bat calls in order to identify which type of bat was most likely to have made the call.

The really clever part from a technical perspective is that all of this processing can be done on the device using one of Intel’s Edison chips. Rather than having large amounts of audio transmitted back to a centralised system for storage and analysis, Intel are employing ‘edge processing’, processing on the device at the edge of the network, to massively reduce the amount of data that needs to be sent over the network back to their central data repository. Once the spectrogram has been produced the original sound files are immediately deleted as no longer required. Combined with the fact that sounds within the range of human speech and below 20kHz are ignored by the algorithms that process the data, this ensures that the privacy of passersby is protected.

This is a fascinating project and it has been great having access to such an unusual data set. Further work here can focus on visualising previous evenings data in time-series to better understand patterns of bat activity over the course of the study. We also hope to investigate the use of sonification by incorporating recordings of typical bat calls for each species in order to create a soundscape that complements the visualisation and engages with the core sonic aspect of study.

Kind thanks to Sarah Gallacher and the Intel Collaborative Research Institute for providing access to the data. Thanks also to the Queen Elizabeth Olympic Park for enabling this research. For more information about bats on the Queen Elizabeth Olympic Park check out the project website: Nature Smart Cities.


CleanSpace: Mapping Air Pollution in London


Today I received a personal air quality sensor, the CleanSpace sensor tag. The device is a carbon monoxide (CO) sensor which is designed to be carried by the user and paired with the CleanSpace Android or iOS app via blueetooth. While the sensor takes readings the app provides real time feedback to the user on local air quality. It also pushes the anonymised sensor readings to a cloud server which aggregates them to create a map of air quality in London.

As well as providing data for analytics the app is intended to encourage behaviour change. It does this by rewarding users with ‘CleanMiles’ for every journey made on foot or by bike. The clean miles can then be exchanged for rewards with CleanSpace partner companies and retailers.

Another interesting aspect of the project is that the sensor tag is powered using Drayson Technologies’ Freevolt. This enables the device to harvest radio frequency (RF) energy from wireless and broadcast networks including 3G, 4G and WiFi. In theory this means that the device can operate continually without needing to have its batteries recharged because it can draw energy directly from its environment. In this way the CleanSpace tag provides a perfect test bed for Drayson’s method of powering Low Energy IoT devices.

The project kicked off with a campaign on Crowdfunder last autumn which raised £103,136 in 28 days. The campaign was initiated shortly after the announcement of results from a study at Kings College which found that nearly 9,500 deaths per year could be attributed to air pollution. Two pollutants in particular were found to be responsible: fine PM2.5 particles in the air from vehicle exhaust along with toxic Nitrogen Dioxide (NO2) gas released through the combustion of diesel fuel on city streets. While the CleanSpace tag does not measure PM2.5 or NO directly it is believed that recorded levels of CO can provide a suitable surrogate for other forms of air pollution given their shared source in car fuel emissions.

While the UK government are under pressure to clean up air pollution from the top-down, Lord Drayson who leads the CleanSpace project argues that there is also need for a complementary response from the bottom up:

“I think the effect of air pollution is still relatively underappreciated and there is work to do in raising awareness of the impact it has.”

“Yes, the government has a role to play, but this isn’t solely a government issue to tackle. The best way to achieve change, and for legislation and regulation to work, is for it to grow from and reflect the beliefs and behaviours of the general public as a whole.”

I’m looking forward to seeing what the device reveals about my own exposure to air pollution on my daily commute. It’ll also be interesting to see how my contribution fits in with the broader map being built up by the CleanSpace user community. After collecting some data I’m keen to compare the apps output with the data collected by the London Air Quality Network based at King’s College.

I’m a card carrying walker. At the same time I’m struck by the paradox that every CleanMile walked or cycled is essentially a dirty mile for the user. I can see the device and app appealing massively to those who already walk and cycle, and want to contribute to raising awareness on the issue of air pollution. However, with the sensor retailing at £49.99 the CleanMile rewards will have to be sufficiently compelling to encourage a wider base of new users participate, especially if the project is expected to have a genuine impact on the way they commute. Of course, it has to start somewhere! It’s an exciting challenge so I’m looking forward to seeing how it goes.