Serval Sensor

Sound recognition - live in Amsterdam!

Below is a translated article about our sound event recognition sensor SERVAL. To speed up development we open-sourced it, resulting in a great collaboration with the IoT Sensemakers AMS.

Enjoy the read!

How does the Marineterrein sound?

10 AUGUST 2021

Noise pollution is a big problem in the city. But to tackle it, you first need to know what exactly causes the noise. At the Marineterrein Amsterdam, tests are now being conducted with a sensor that can classify sounds and thus pinpoint the source. And this with technology that originated in the jungle to stop poachers.

It all started with a gunshot in the jungle of Laos, followed by the sound of a boat sailing away. It made Jan Kees Schakel of Sensing Clues realise that it is easy for poachers to make off with their 'loot' under cover of night. But he also realised that the sound the poachers produce is the way to stop them.

Sound sensor

Humans are noisy creatures', says Jan Kees. Basically any sound we make - talking, driving a vehicle and certainly gunshots - carries far and can therefore be picked up well by a sensor. A big advantage over cameras, which are limited by what their lens can 'see'. A sound sensor can help conservationists map out what and where is happening at any given time. After all, if voices can be heard in the jungle in the middle of the night, you can be reasonably sure that something is wrong.'

Complex

That sounds good, but it is easier said than done. Until about five years ago, only the number of decibels of a sound could be detected, but the sound could not be classified. In other words, a sensor could indicate that a loud sound was being produced somewhere, but not whether it came from a slamming car door or an elephant. And it is extremely difficult to be able to make that distinction,' says Jan Kees. You need an enormous database of sounds which then serve as a frame of reference for a complex algorithm to classify sounds'.

Practical challenges

'But since 2016, artificial intelligence and machine learning has taken off,' he continues. 'The technology is getting better and better and we can now recognise multiple sounds with one algorithm. But it is still important to have a large database of sounds and there are also practical challenges. There has to be power, a good internet connection and the hardware around the sensor has to be able to withstand the elements. To get everything working optimally we need to do a lot of testing.

Test location: urban jungle

Since testing sound sensors in the jungle is expensive and complicated, Jan Kees decided to do it closer to home. In the urban jungle to be precise. The Marineterrein has recently been equipped with a sound sensor that maps out city noise and noise pollution. Jan Kees joined forces with Sensemakers AMS, an old friend of ours who has been active at the Marineterrein for years, measuring and interpreting the water quality in the inner harbour, for example. With their combined knowledge, they developed a test set-up that will provide insight into the sound of the Marineterrein, and the extent to which there is nuisance.

The sensor of Sensing Clues and the IoT Sensemakers AMS

The sensor of Sensing Clues and the IoT Sensemakers AMS

Training algorithms

With this project, we can gain a wealth of experience in training our algorithms', says Jan Kees. That is useful for conservationists, because in the jungle we look for the same kind of sounds as here. Voices, laughter, the sound of car engines and doors slamming. But with what we do here now, we can also tackle nuisances in the city. Noise pollution can reduce residents' enjoyment of living and even cause stress. But it is often difficult for people to say exactly what is bothering them. By classifying urban noise, we can pinpoint the exact time and source of various noises and use this information to tackle the problem in a targeted way.

Alarming noises

According to Jan Kees, this mainly concerns intrusive, loud noises. As a resident, you often no longer hear overflying aircraft or trams, you get used to it. But sudden, loud noises trigger us. It is still deeply ingrained in our cognition to be alarmed by such sounds, as a reaction to possible danger. Think of accelerating scooters and alarms, but also of bicycle bells. By classifying these types of sounds, we can pinpoint exactly where the nuisance comes from. It is important that we do this while preserving privacy. The sound is processed on the sensor and not stored. Only the sound labels, such as 'moped' or 'scooter alarm', are stored. So only labels remain, and no sound.'

Jungletech also for a liveable city

With the knowledge gained from this test at the Marineterrein, this technology can be used on a larger scale in the city in the future. In squares, in entertainment areas and even in individual cafés, to make visitors aware of the potential nuisance they are causing. In this way, Jan Kees hopes that his 'jungle technology' can contribute to a liveable city. But of course we eventually want to bring the lessons we learn here back to the jungle. That will require some further development: in the bush there are no power outlets or wifi, so we have to find good and cheap solutions for that. The most important thing is that the technology remains affordable for conservationists, so that they can always stay a step ahead of poachers.

Sensing Clues

Sensing Clues is a non-profit foundation and largely relies on volunteers. You can support Jan Kees' fight against poachers by making a donation. Do you have the knowledge and skills to contribute to this project? Then get in touch with Sensemakers AMS. Electronics engineers and people who like to get started with data analysis and visualisation are particularly welcome.

Text: Sjoerd Ponstein

Translated by Deepl.com

Sponsor our open source projects!

CAIMAN

In the Kaggle iWildcam 2021 competition the species recognition and counting algorithm of the Sensing Clues team became split-second second. To increase its spread and impact we recently open sourced the project. With the funds we receive from sponsors we integrate results of CAIMAN in our WITS-platform, which increases the value of these images tremendously.

OpenEars & SERVAL

With our volunteer friends of IoT Sensemakers Amsterdam we have developed a highly sophisticated sound recognition sensor. It recognises many different sounds related to the presence of people, ranging from gunshots, motorbikes, trucks, chainsaws, music, barking dogs, cattle, and other. The sensor is currently being tested in the city jungle of Amsterdam. To be ready for monitoring and protecting the jungles of Africa, Asia and the Amazon a few more development steps have to be taken. Your sponsorship brings that reality closer!

Oh yes, OpenEars is the name of the sensor, hardware and all; SERVAL is the name of the sound recognition algorithm that we created. And both our open source.

Protecting the lion in Africa, starts at Leidseplein in Amsterdam

Protecting the lion in Africa, starts at Leidseplein in Amsterdam

Dutch newspaper ‘Het Parool’ interviewed Sensing Clues founder Jan Kees Schakel about our Serval Sensor, the Amsterdam Sounds project and Sensing Clues. Read the full article right here.

Sound sampling the jungle!

Sound sampling the jungle!

Automated real-time recognition of sounds is a powerful means to inform rangers of potential illegal activities in large nature reserves. Many illegal activities are accompanied with noise, varying from engine sounds to gunshots, and from cattle to dog sounds. They can all be used to alert rangers.

OpenEars is a fact!

Breaking News!

We open sourced our Sound Event Recognition sensor and started working with IoT Sensemakers Amsterdam to boost its development and use.

Yesterday night already, participants managed to produce their first fully operational electronic ears!

In the city jungle of Amsterdam we’ll be using OpenEars this summer to assess noise pollution. In the process we’ll dummy proof the sensor and make it more energy efficient.

Once we’ve achieved that, OpenEars will be provided to rangers working in the actual wilderness to protect endangered species like elephant, rhino and tigers.

The source code can be found at github / SensingClues / OpenEars. Developers interested in helping us with the development of the sensor, are encouraged to contact us!

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1st DIY sound sensor engineering night!

The SERVAL sensor is still very much a Research & Development project. Before we can deploy the sensor in the bush to detect sounds related to poaching, illegal logging, and so on, considerable efforts are needed. To this end, we sought and found opportunities to speed up the development.

IoT Sensemakers Amsterdam

After a few introductory meetings, we had our first engineering night with IoT Sensemakers Amsterdam. Great fun! And successful, as the participants succeeded in mastering the first step: prepare and startup the existing prototype!

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In the next sessions, we will be working on:

  • Testing other microcomputers to run the neural network and reduce power consumption.

  • Testing setup with another (cheaper) microphone.

  • Adding a LoRa-module.

  • Create a cheaper yet robuust housing.

The result we aim at is a user manual describing the various parts of the sensor and the assembly process. With this manual everyone interested can build his own sensor.

We made the software open source, thus allowing you to participate and contribute to its development – which of course, is much appreciated!

Amsterdam Sounds Project

In March / April the Amsterdam Sounds project will start. In this project, which we run in partnership with De Waag, the City of Amsterdam and the Ombudsman Metropool Amsterdam, citizens will be involved in assessing noice pollution in their own neighbourhood.

To assess distinct sound classes, such as scooters, car horns, shouting, and other noises, the SERVAL sound sensor of Sensing Clues will be used. Together with the various neighbourhoods we will be collecting sound samples, that will be used to train our sound classification model.

The output of this “city jungle” project will help us to ready the SERVAL sensor for the real jungle. Both in terms of hardware, software, and sound classification algorithms.

For now, thanks IoT Sensemakers Amsterdam! To be continued!

DataLab for Wildlife Protection

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More species are being threatened with extinction than ever before. To protect them we need to bring together and boost our strengths!

In regular life we use technologies to tackle all kinds of problems. So should we when it comes to the protection of wildlife.

To accelerate data-driven innovation, Sensing Clues, together with Nieuwegein CityDIKW Intelligence and Bluemine, set up the Nieuwegein Datalab (NGDL).

The DataLab is a meeting space and hands-on laboratory for everyone interested in Data Science, Internet of Things (IoT) and Artificial Intelligence. A space to experiment, to develop and challenge new ideas.

Working together with professionals, scientists, and students, Sensing Clues uses the DataLab as incubator for data driven solutions for the protection of wildlife.

Curious? Below are two of the projects we are working on:

  • Sound Event Recognition for Vigilance and Localisation (SERVAL)

  • Wildlife Crime Analyst Toolbox (WildCAT)

Want to join one of our projects or to start a data-driven wildlife protection project of your own? Just drop us a note to start your expedition!

Data Scientists saving rhinos!

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On Friday 7th July 2017 JADS will host the first-ever Wildlife Hackathon. During a full day of data- and brain-crunching activity, no less than 50 students and two data science teams of KPN and DIKW will dedicate themselves to find ways in which data can save some of the most threatened species in Africa.

The competing teams will be presented with two challenges. One presented by the Resource Ecology Group of Wageningen University. The other by Sensing Clues.

The challenge presented by Wageningen University is aimed at the preservation of rhino’s, by finding correlations between the time-spatial distribution and movement of zebra herds versus the presence of poachers wandering through the park. The brilliance of this  approach is that the rhino’s do not have to be equipped with radio-beacons, which are easy to detect by professional poachers.

The challenge presented by Sensing Clues is aimed at reducing the conflict between humans and elephants. By accurately recognising the sounds of approaching elephants, villagers can be warned in time, thus preventing deadly confrontations (see also: SERVAL sensor). In this hackathon the students will be challenged to outperform the classifier created by Hugo, our most experienced data scientist.

This unique event is the result of a close collaboration between JADS and a Game Reserve in South Africa. Journalists interested in joining the event may contact Patricia Beks (p.beks at tue.nl / tel. + 31 (0) 6 31 242 757).

Detecting poachers through Sound Event Recognition

Anti-poaching

In 90 seconds this video shows you how the SERVAL can be used to detect threats, such as poachers or illegal loggers.

Human-Wildlife Conflict

Another promising application of SERVAL is the mitigation of the human-wildlife conflict. Habitats of elephants shrink, seducing them to roam into the land and villages of farmers living near nature reserves. This is causing serious trouble. Villagers loose their crop, or worse, get killed. In retaliation, elephants get poisoned or shot. By identifying and localising elephants before they enter the human territories, rangers may be in time to keep both the villagers and the elephants safe.

For this project, we are working closely together with:

  • Karol Piczak of the Warsaw University of Technology,

  • Angela Stoeger-Horwath of the Dept. Cognitive Biology, Vienna University,

  • Matthias Zeppelzauer of the St. Pölten University of Applied Science,

  • Peter Wrege of the Elephant Listening Project at Cornell University, and

  • Blaise Droz, independent nature journalist and videast.