The Cacophony Project is fortunate to have many talented people helping to move it forward.
This week we say goodbye to Huub Nijs who found us while visiting New Zealand on a working holiday from the Netherlands.

Grant Ryan from the Cacophony Project was featured on Radio New Zealand's Nine to Noon show on Friday morning.

linux.conf.au, the annual local conference centred around the Linux operating system, was held last week in Christchurch. Linux is the basis for almost everything we create at the Cacophony Project, and Clare and Menno were there to talk about where the project is at and where it's heading.

The Cacophony Project is an ambitious project with many moving parts. It can be difficult to understand what our technology does and how the various components of the project fit together.

We are often asked the status of the project so we thought it would be useful to share a table which highlights how we think about our progress. These are a set of milestones that need to be achieved to make New Zealand predator free. We define various phases that each milestone moves through as progress is made.

On November 4 2018, the Cacophony Project was privileged to become a signatory of the Banks Peninsula 2050 Predator Free Initiative. Along with key personnel from DOC, Ecan, Christchurch City Council, Banks Peninsula Iwi and Banks Peninsula Conservation Trust, the Cacophony Project's Clare McClennan was present to participate in the signing ceremony held at the Living Springs amphitheater. This historic partnership aims to focus and coordinate efforts to eliminate invasive predators on Banks Peninsula.

Early October 2018 we received our Cacophonometer at our Sandspit home. The setup process was very simple with the app having been pre-installed and the main next steps being getting our account created online and the device registered. The location we chose was around 20 meters from our house (a site with power available) and a small WiFi extender soon fulfilled the coverage required to ensure the upload process was reliable. We soon had plenty of recordings to sample with the ‘meter following the pattern set by the software – i.e. greater intensity of records around dawn and dusk.

The thermal video footage from the Cacophonator devices has proven to be invaluable for machine learning and studying predator behaviour. Occasionally, however, we noticed that recording for some animals was starting later than it should. In this article we discuss the reasons why this was happening and what we have done to improve our animal detection algorithm.

For a few weeks I've been using one of the thermal cameras we are working with here at The Cacophony Project. It is dubbed a "Cacophonator" because eventually, it won't just take pictures.

The video in this link shows a visual representation of the contributions to the software components of the project over time. The visualisation is based on source code changes pushed to Github and shows the areas of the software being worked on and the people involved.

The Cacophony Project started with the development of a simple cell phone based tool that can measure birdsong so there is an objective measure of how well birds are doing as predator control is rolled out. This product is now ready to be more widely tested around New Zealand.

Up until now we've typically run our devices on mains power. We've preferred sites which are near native bush but have access to a wall socket (sometimes with long extension cords!). This has gotten us quite far in terms of testing our prototypes and gathering footage to train our machine learning classifier but obviously isn't going to be a long term solution. Being able to run on battery power opens up a huge range of new areas to our devices.

I am Dr. Ayesha Hakim, a computer scientist with an aim to use my skills to do something 'Good for Nature'. I joined Cacophony to contribute towards preserving New Zealand's birds in the wild. My research interests include behaviour analysis using machine learning techniques and producing pretty graphics to visualise the complex data. To be specific, I am interested in recognition and behaviour analysis of humans and birds using audio and visual signals.

The Cacophony Project has very long-term goals to enable us to eliminate 100% of predators. It’s easy to look at what we are doing and assume that this will never work in the depths of the remote bush. While we acknowledge that there are many steps before we achieve that capability, the tools developed while getting to that end goal will be useful for other important parts of the problem.

Hi I’m Clare and I’m the newest member of the core Cacophony Project team.
I’m a passionate outdoor adventurer, native flora and fauna lover and an experienced software developer. I love the interesting and diverse nature of the Cacophony Project and find it exciting to be able to work on a project aligns perfectly with my values and interests.

At first look it seems like it should be easy to work out how effective traps are. Our first way of measuring it was very simple - how often do we see animals around a trap compared to how often they are caught by the trap. This is too simplistic: with enough time an animal will eventually wander into a trap and be caught. Any device with some chance of killing/luring will have a 100% success rate given infinite time. Therefore, time should be one of the parameters for a device’s effectiveness.

You have to love the way journalists make a headline. They get most of the details of the actual project pretty right though.

Below is a talk from the recent New Zealand AI conference. It gives an up-to-date summary of the project with particular reference to how we are using Machine Learning.

A critical component of our Cacophonator devices is the FLIR Lepton 3 thermal camera. It's our eyes in the dark as we look for invasive predators. As discussed previously, reliably extracting video frames out of the camera has been a challenge. Our software would often "lose sync" with the camera, resulting in lost video data.