serval

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.

Machine listening is a very new and fast-developing field of expertise, heavenly based on machine learning. To design and deploy a sensor capable of recognising many different types of sounds in realtime, many engineering hours and development cycles are needed. Hence, we chose to develop it in the jungle which we call our home, before we deploy it in the actual jungle.

current status

Together with volunteers of the IoT Sensemakers Amsterdam, we have improved the first prototype of our SERVAL sound sensor. Meanwhile we started a citizens science project with the City of Amsterdam, the Ombudsman, and De Waag, to address the problem of noise pollution.

This Thursday we started sound-sampling the Amsterdam City jungle! Together with friends from de Waag and IoT Sensemakers Amsterdam we collected many hours of recordings of sounds that are known to bother people.

This summer we’ll use the collected samples to train the SERVAL sensor, after which it will be deployed in the city to assess and address noise pollution in a much more meaningful manner then ever before.

The first results are expected by the end of this year. Once the technology has been proven in the city jungle, we’ll bring it to the jungles and savannes of Africa and Asia to help protecting wildlife.

We can’t wait!

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!

img_20190403_185634497.jpg
img_20190403_210958758.jpg
img_20190403_201202797.jpg
img_20190403_200603454.jpg

Data Scientists saving rhinos!

jads-wildlife-hackathon_orig.jpg

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,

  • Shermin da Silva of Trunks & Leaves,

  • 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.