4000 euro for wildlife risk prediction model!

Today the Dutch MarkLogic team ended their MarkLogic Charity Bike Ride, which took them from London to Amsterdam to Utrecht. The weather was good and the spirits high!

By the end of their 3-day journey they had raised 4000 euro for the protection of wildlife!

The Dutch MarkLogic team handing over the check to Jan Kees Schakel and Hugo Koopmans of Sensing Clues Foundation

The Dutch MarkLogic team handing over the check to Jan Kees Schakel and Hugo Koopmans of Sensing Clues Foundation

The donation will be used to extend the Wildlife Intelligence platform with a risk prediction model, which wildlife rangers can use to outsmart poachers and optimise the timing and routes of their patrols.

We need 7.000 euro to complete the risk prediction model, so, if you want to help, please find the Donate button on our website!

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!

Marsican Brown Bear

Imagine if you could accurately predict the movements of a highly endangered animal species, hours or days in advance. For those engaged in the conservation of that species, such information would be invaluable.

The Apennine Mountains is a large mountain range in central Italy. The mountain slopes are mossy and covered with huge centuries-old beech trees. The area is home to large populations of deer species and wild boar, who share their habitat with wolf, semi-wild horses and cattle.

Its most famous resident is the Marsican brown bear, which is endemic to this region.

Together with the experts of Rewilding Europe, Sensing Clues will be working on improving knowledge about the whereabouts and activities of the Marsican brown bear. We’ll use this information to design predictive models that can be used to prevent harmful interactions between local residents and bear, and thus contribute to their successful co-existence.

Marsican Brown Bear. Photo by Bruno D’Amicis, Rewilding Europe

Marsican Brown Bear. Photo by Bruno D’Amicis, Rewilding Europe


Read more about the project at the website of Rewilding Europe.

First results of frontier oost!

So proud to present to you the first tangible contribution of our new Solution Partner - frontier oost - a complete new version of our site!

The development of our tools for wildlife protection depends on people like Yorinde, Marco and Jimmy of frontier oost, who donate part of their time and expertise to do good.

If you, too, find our mission worthy your support, don’t hesitate to hit the donation button! For just 25 euro you contribute to the protection of 5 square kilometer, harbouring 100s of animals!

Together we turn wild spaces into safe havens!

frontier oost joins forces!

frontier oost, founded only 6 months ago by Marco, Yorinde and Jimmy, is the seventh organisation that officially joins forces with Sensing Clues to turn wild spaces into safe havens!

By applying their knowledge and skills about design thinking and incremental development, it’s their mission to design for people with the technologies of tomorrow. And that’s what they will be contributing to our growing coalition for wildlife!

Last Friday we signed the agreement. A memorable moment!


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!


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!

screen-shot-2019-03-08-at-09.02.42 (1).png

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!

IN THE NEWS – March 2019


Click here the read the original article in the newspaper.


Als politie-onderzoeker kent hij de modernste technologie die wordt ingezet bij opsporing. Met zijn stichting zet Jan-Kees Schakel die in om stroperij in wildparken te bestrijden. Laurens Verhagen, 1 maart 2019, 9:17

De luide knal van een geweerschot. Jan-Kees Schakel en zijn vrouw worden midden in de nacht opgeschrikt in hun bamboehut in de jungle van Laos. Ze zijn op dat moment de enigen in het resort. Verder alleen de herrie van de natuur. En dat schot dus ineens. Ze wachten op wat komen gaat. Angstige minuten. Een kwartiertje later horen ze een bootje wegtuffen op de nabijgelegen rivier, richting bewoonde wereld. Het kan maar één ding betekenen, weet Schakel: stropers. Het incident vormt het begin van zijn stichting Sensing Clues. Als onderzoeker en strategisch adviseur bij de politie heeft hij dan al vele jaren ervaring met het gebruik van de modernste waarnemingstechnologieën die kunnen worden ingezet bij opsporing. Dat kunnen camerabeelden zijn, maar ook Twitterberichten: alles wat maar kan helpen bij het opsporen van criminelen of het zo snel mogelijk signaleren van een crisissituatie.

In zijn hut in de jungle van Laos beseft Schakel dat precies dit soort informatie hard nodig is om de natuur te beschermen. Hier kan hij zijn oude en zijn nieuwe werk combineren; voordat hij bij de politie terechtkwam, heeft Schakel jarenlang in de tropen gewerkt als natuurbeschermer. Met zijn stichting wil hij parkwachters voorzien van de technieken waar ook de politie mee werkt. Sensoren, analyseprogramma’s, apps: alles wat maar kan bijdragen aan de strijd tegen stropers. Als het de natuurbeschermers aan één ding ontbreekt, is het real time-informatie.

Jan-Kees Schakel (links) met een parkwachter in Nepal. Beeld Sensing Clues

Jan-Kees Schakel (links) met een parkwachter in Nepal. Beeld Sensing Clues

Schakel kwam er snel achter wat het grote probleem is: er zijn gadgets genoeg, maar die werken vaak niet goed samen. Of ze zijn gebruiksonvriendelijk. Het gevolg is dat veel informatie nog altijd op traditionele wijze wordt overgebracht; mondeling, als de rangers elkaar ’s avonds bij het eten treffen. Of via opschrijfboekjes, die pas na drie maanden door iemand in de computer worden ingevoerd. De stroper is dan al lang en breed gevlogen. 

Een deel van de oplossing is volgens Schakel de app van Sensing Clues. Schakel, die inmiddels nog maar de helft van de tijd bij de politie werkt en de helft van zijn inkomsten heeft ingeleverd, laat de app zien. Eenvoud staat voorop; de ranger kan zijn rapportages doen via een aantal icoontjes. Zo kan hij aangeven dat hij resten van een vuur heeft gevonden, of een strik of bandenspoor. ‘Rangers weten vaak niet of iets van belang is of niet. Logisch ook; pas in combinatie met andere sporen kan de grote lijn duidelijk worden.’ 

Schakel noemt als voorbeeld de vondst van een kapot kapmes door ranger 1 en een paar dagen later in hetzelfde gebied batterijen van een zaklantaarn door ranger 2. ‘De combinatie van zaklamp met kapmes kan duiden op het stropen van giraffen’, weet Schakel. ‘De ene stroper verblindt de giraffe met een krachtige lichtbundel en maakt lawaai met een ratel, waarop het dier in verwarring blijft staan. Zijn collega benadert de giraffe van achter en hakt de achillespezen door, waarop het beest ter aarde stort.’ Het vlees van de – beschermde – giraffe wordt vervolgens op de markt verkocht als ‘bush meat’, goedkoper dan koeien- of geitenvlees.

Vele uren mankracht

‘Alles begint met de waarnemingen. Die kunnen van parkwachters zijn, maar ook van andere mensen die je vertrouwt, zoals boeren, gidsen of toeristen.’ Een ander belangrijk onderdeel is het data- en analyseplatform. Hier komen alle gegevens binnen. Schakel had dit nooit kunnen ontwikkelen zonder de hulp van allerlei partijen die hij vanuit zijn politiewerk al kende. Consultants, juristen, datawetenschappers, vormgevers en programmeurs hebben allen belangeloos hun steentje bijgedragen. Door software zonder licentiekosten beschikbaar te stellen, maar ook via vele uren mankracht. Het resultaat is een systeem dat iedereen snapt. De ranger ziet één duidelijke kaart waarop alle informatie kan worden getoond. Dit alles met als doel meteen actie te kunnen ondernemen.

Verder zijn ook sensoren hard nodig, want mankracht alleen is nooit voldoende. In de Rukinga Wildlife Corridor in Kenia werken bijvoorbeeld zo’n 120 rangers (in groepen van 8) op een gebied van 220 duizend hectare. Dat is maar iets minder dan de provincie Noord-Holland. Op strategische plekken kunnen sensoren worden achtergelaten. Daar komt veel bij kijken, want ze moeten via zonnepanelen (of eventueel een batterij) aan energie komen, maar mogen tegelijk niet opvallen. 

Schakel verstopt een zonnecel voor een sensor in een park in Kenia. Beeld Sensing Clues

Schakel verstopt een zonnecel voor een sensor in een park in Kenia. Beeld Sensing Clues

Sensing Clues ontwikkelt nu drie typen sensoren: voor het registreren van kunstmatig licht, van elektronica (bijvoorbeeld de signalen die mobieltjes uitzenden) en voor menselijk geluid. ‘Stropers maken veel lawaai’, weet Schakel. ‘Ze wanen zich onbespied omdat het gebied zo groot is. Ze maken dus gerust een vuurtje en zetten de radio aan.’ 

Herbert Prins, hoogleraar Natuurbeheer aan de Universiteit van Wageningen, gelooft enorm in het gebruik van sensoren en AI om stropers op te sporen voordat ze een misdaad hebben begaan. Het is de reden dat hij Sensing Clues ondersteunt door in de raad van toezicht plaats te nemen. De natuurbescherming is volgens hem de laatste decennia ‘gemilitariseerd’, een slechte ontwikkeling. Volgens Prins moet de geweldsspiraal – aan beide kanten vallen dodelijke slachtoffers – doorbroken worden, wat mogelijk is door technologie slim in te zetten. Hij noemt de speciale trackers waaraan het Hilversumse ict-bedrijf Sodaq werkt. Deze worden aangebracht op bijvoorbeeld zebra’s. Door het gedrag van een kudde te analyseren, kan met ‘een waanzinnige precisie’ voorspeld worden of er stropers in de buurt zijn. ‘Zebra’s reageren anders op stropers dan op parkwachters of toeristen. Ze ruiken gevaar als ze mensen zien die sluipen of gewoon wandelen en gedragen zich daar dan ook naar door bijvoorbeeld hard weg te lopen.’

Beeld Eline van Strien

Beeld Eline van Strien

Toys for boys

Hoe veelbelovend al dit soort sensoren ook zijn, het zijn geen wondermiddelen, benadrukt Schakel. ‘Je hebt niets aan gereedschap als het niet onderdeel is van een hele kist. Alles moet goed op elkaar zijn afgestemd.’ En juist daar gaat het vaak mis, volgens Schakel. Hij ziet spectaculaire en mediagenieke voorbeelden voorbijkomen. Camera’s in de hoorn van een neushoorn, drones, noem maar op. ‘Dat ziet er allemaal prachtig uit, maar er is niet altijd goed over nagedacht.’ In de woorden van Prins: toys for boys

Daarom werd Schakel in eerste instantie ook met de nek werd aangekeken toen hij bij parken aanklopte: wéér zo’n westerling die met een gadget komt aanzetten die alles gaat oplossen. Pauline Verheij, programmamanager Wildlife Crime bij dierenwelzijnsorganisatie IFAW, is ‘heel enthousiast’ over het gereedschap van Sensing Clues. ‘Vaak wordt vergeten wat de basisproblemen zijn. Stroperij floreert in landen waar gebrek is aan capaciteit, geld en politieke wil. En waar veel corruptie is. Rangers moeten vaak werken onder slechte omstandigheden, waardoor ze ongemotiveerd zijn. Er is geen benzine, geen uitrusting, geen fatsoenlijke kleding. Dan kun je wel met de nieuwste technieken komen, maar dat lost niets op.’ Terwijl techniek volgens Verheij wel degelijk kan helpen om de bestrijding van stroperij effectiever te maken. ‘Ik geloof erin als het eenvoudig en laagdrempelig is in het gebruik.’ Sensing Clues voldoet daar volgens haar aan.

Voor die gereedschapskist van Sensing Clues moet trouwens nog wel betaald worden. Veel is het niet: een paar duizend euro per jaar voor ondersteuning. Sensing Clues heeft nu afspraken met twee beschermde gebieden: Rukinga Wildlife Corridor in Kenia en Phudunda in Zimbabwe. Dat is het begin, als het aan Schakel ligt: ‘We hebben de ambitie om honderden parken te helpen.’ Zorg is er ook, over de beveiliging van de webomgeving: ‘Stroperij is een miljardenbusiness. Zodra stropers zien dat dit een succes is, gaan ze alles uit de kast halen om ons plat te leggen, zodat rangers hun werk niet meer kunnen doen. We moeten er rekening mee houden dat we van alle kanten worden aangevallen.’ Schakel zoekt dus nog hulp van de beste cybersecuritybedrijven. De constante wapenwedloop tussen beschermer en stroper zal ook op internet worden gevoerd.

Cluey is ready for protecting wildlife!

Beta-testers are invited

Celebrating the launch of the Platform for Wildlife Intelligence

Celebrating the launch of the Platform for Wildlife Intelligence

After years of development and testing, Wildlife Works and Phundundu Foundation are among the first to use our Platform for Wildlife intelligence in the field. With the tools that the platform provides, rangers learn what is exactly going on in the field, which enables them to show up in the right place at the right time to stop poachers in their tracks.

The beta-tests are scheduled to continue till Summer 2019. NGO’s working in the field are invited to help us testing the Platform. If you are Interested you can contact us here!


Why MarkLogic? Customers explain..

For some it’s technical magic, for us it’s all about strengthening rangers using cutting edge technologies in harsh and demanding environments.

At 0.33 minutes of this video, Brigade General of the Ministry of Defence explains in clear language the operational value of technologies like MarkLogic in warfare.

If you can’t wait to see how Sensing Clues is using it, jump to 3.19 minutes!

RangerCampus and Sensing Clues join forces!


The mission of the Ranger Campus Foundation is to protect wildlife by strengthening law enforcement in protected areas. They do so by developing and providing law enforcement training and e-learning for wildlife rangers. Through their fieldwork, RangerCampus has in-depth knowledge of, and experience with, the multitude of challenges that rangers face. We are therefore happy to announce that RangerCampus has become Field Partner of Sensing Clues Foundation!

Our joint aim is to strengthen the information position and operational capabilities of rangers. Where Sensing Clues and her technology-partners develop the required technologies, Ranger Campus helps us to identify technology requirements, organise field tests, provide us with first-hand ranger-feedback, and develop training materials where needed.

Together, we turn wild spaces into safe havens!

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 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!


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


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.


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!

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

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!

Our hawks have left their nest – mission completed!

Mission completed! This weekend the young hawks stretched their wings and made their first flight.

For almost two months the rangers in the Southern Netherlands have been on the alert for poachers, as the nest has been robbed for several successive years. Local bird lovers complained, but the problem was difficult to tackle. Attempts to catch the poachers through camera traps failed, as the cameras were stolen.

This year a Trespasser was hidden near the birds-nest to notify the rangers when people would come near. The sensor triggered 16 times. Based on a smart algorithm we are able to determine whether a detected person is bypassing or lingering at the scene. We were especially interested in the latter, which happened twice. The first time was on the first of June, when the young were still very small. Great was our relieve when it proved to be one of our rangers checking whether the birds were still safe. The second time foresters were busy marking trees near the nest.

Now the birds have left their nest on their own – the first time since years. We are so happy about it! A pity that we didn’t catch a poacher, but so be it. The sensor operated well and unattendedly for over 6 weeks. The rangers are enthusiastic about them as the sensors can distinguish between people and other moving targets and can be placed completely out of sight (see photo below – just try to find it 

Time to celebrate and move on to the next project!


The clock is ticking…

About one week to go before the young of our hawks will fly out and discover the world! So far we managed to shield off the poachers, who have been stealing chicks for years.

It’s a project in which we learn while doing. As we knew, in fast-response organizing every second is of the essence. Easy to say. Quite complex to accomplish technically.

Today we scrutinized the process steps from signal detection to alert. A process which from sensor to end-user app covers over 15 time critical components.