DataLab for Wildlife Protection

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 City, DIKW 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!

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 / tel. + 31 (0) 6 31 242 757).

Detecting poachers through Sound Event Recognition



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.


Smart Vision update

Noah and friends have done it! The Open CV (computer vision) is running on a Raspberry Pi. To ensure that the system performs well in real-time they had to “overclock” the system and to add a heat-sink to prevent the chip from burning. The result is a fast, low-cost and low-energy smart camera that can be used for wildlife census and anti-poaching missions.

The recognised ‘objects’, in our case, are humans, elephants, tigers, and other species. The outcome is communicated with Cluey to inform park rangers in real-time. The data may also be used by census-researchers. In that case the classified images may be collected periodically.

Below you see the sneak-preview of the cloud-based smart-cam training console. This console may be used by experts or the public to improve our classifier (for the experts: we use a mix of classic learning, machine learning, and deep learning). Once the detection accuracy of the smart-cam is sufficient, the sensor can be placed in the field. To reduce communication cost, only the class will be send. To increase confidence in the system, a thumbnail of the recognised object may be send as well.

sneakpreview smart cam.png

Can’t wait to experiment with the smart cam? Feel free to contact us to discuss how we can speed up time to the field!

DIY Smart Computer Vision

The problem

If you have a camera to detect burglars, an alarm system to detect opening doors, and a smoke detector to alert you in case of fire, wouldn’t it be nice if all these systems could be presented to you through one simple app? If you already have an integrated system like that, you probably bought all of the components at the same supplier. Adding third-party or Do-It-Yourself (DIY) sensors, or combining the data with other data sources, such as weather stations or the GPS-position of your mobile phone, is probably hard or impossible. Options to combine the data, however, would enable you to make your systems really smart…

The solution

To allow you to connect any type of sensor you wish, we are developing an open source Application Programming Interface (API). Any hobbyist or programmer can use it to connect his of her own device to the SCCSS-sensing platform. From there, the data may be presented in Cluey or WildCAT, or exported to CSV, XML or JSON, for further analysis.

Low-cost Smart Computer Vision Camera

A first trial project has been adopted by 4 students of Technasium Keizer Karel College Amsterdam. Noah, Robin, Celio and Dimme have the ambition to turn a standard webcam into a low-cost Smart Computer Vision Camera. That’s a camera which does not just take pictures, but which can be trained to takes pictures only when a person walks along, or a dog, tiger, elephant, or whatever else it has been trained for. Once the object of interest has been detected, a small image is created and sent to the Cluey-app.

A tough task, involving the mastering of Open Source Computer Vision software on a Raspberry Pi, Python programming, a little engineering, and lots of endurance, fun and enthusiasm!

Noah, Robin, Celio and Dimme expect to finish the project this summer. They will publish the source code and the “How to” in GitHub, thus making it available to the public for free.

The first results are looking good!


Screen print: Noah captured by the team’s engineering masterpiece, the low cost Smart Computer Vision Camera!

Sensing Clues at TEDx!

You should listen to the TEDx-talk I held at TEDxRotterdam last November,

  • if you feel angered about elephants being killed for their ivory,
  • if you want to be challenged to do something about it – by doing what you know best!

Looking forward hearing from you!

Jan-Kees Schakel, CEO Sensing Clues

ps please share the story with your friends!

Sensing Clues goes to Nepal!

After a summer of hardcore development, Sensing Clues is ready for the next step. Together with the Himalayan Tiger Foundation we’ll travel to Nepal to examine and demonstrate the potential of our sensor and real-time intelligence tools. Think of:

  • passage detection,
  • lingering detection,
  • group size detection,
  • first-time seen detection,
  • light-beam detection,

and many other profiles which can be used to inform rangers of alarming occurrences in protected areas. Following is a short summary of what we did this summer.

The Trespasser, a sensor designed to detect electronic devices, has reached it next level of maturity. In a pilot study conducted with the Dutch National Forestry Department we were able to detect the difference between hikers passing a nest of a protected hawk and people lingering near the nest. Based on the number of devices we could estimate the number of persons at the scene. This is an important feat, as “big-5 poachers” often work in groups of 3 to 4 persons. Recognizing the number of people lingering near a waterhole or other critical spots thus gives rangers an early warning of a threatening situation.

Our new Serval-soundscape sensor has passed its first milestones. Data acquisition, a tech-word for recording and storing the sounds in a ready-to-process format, is ready. So is the store-in-memory function that ensures that sounds do not get wasted when connectivity is lost for a while. The next step is to incorporate the recognition algorithms and to establish connectivity. Both are within reach. As soon as time and funds permit we will start field-testing.

Power supply is a critical issue when working in remote areas. As there is no off-the-shelf solar solution that meets our tough outdoor requirements, which includes proper camouflaging to avoid detection by poachers, we needed to develop a tailor-made solution. The good news is: we did. The first results are promising. In two days time the solar panel is able to load a car battery that keeps the sensor alive and kicking for over 6 weeks. Hence, protection operations of 3 to 6 months have become within reach.

In the mean time we experimented with the setup of a LoRa-network. Such networks are comparatively cheap and can be deployed where cellphone coverage is lacking. As with all technology, the road to full-scale use is bumpy. If not properly configured, reaching a proper range is troublesome. Knowing the problem is half the solution. So we are now working on the second half.

All that being said, most of our time was spent on the development of Cluey, our fast-response coordination app, and its backend, which in fact constitutes an affordable sensing-and real-time analytics platform and intelligence tools. Our platform constitutes a dozen servers, software packages, has very high security standards, and is maintained by our engineers. Regularly, such systems are prohibitively expensive for a single park or NGO. By offering the platform as a service, however, we bring it within reach of even the most modest NGO.

Ps. local governmental organisations in the Netherlands have shown an interest in these tools also, which accelerates their development!