An ultimate collar for the largest mammals.
Elephants are mammals of the family Elephantidae and they are the largest existing land animals. They are also keystone species, playing an important role in maintaining the biodiversity of the ecosystems in which they live.
The elephants use their tusks to dig for water. This not only allows the elephants to survive in dry environments and when droughts strike, but also provides water for other animals that share harsh habitats. When forest elephants eat, they create gaps in the vegetation. These gaps allow new plants to grow and create pathways for other smaller animals to use. They are also one of the major ways in which trees disperse their seeds; some species rely entirely upon elephants for seed dispersal. On the savannahs, elephants feeding on tree sprouts and shrubs help to keep the plains open and able to support the plains game that inhabits these ecosystems. Wherever they live, elephants leave dung that is full of seeds from the many plants they eat. When this dung is deposited the seeds are sown and grow into new grasses, bushes and trees, boosting the health of the savannah ecosystem.
But threats to the giant of the forest are numerous. According to the WWF, African elephant populations have fallen from an estimated 12 million a century ago to some 400, 000. In recent years, at least 20, 000 elephants have been killed in Africa each year for their tusks. African forest elephants have been the worst hit. Their populations declined by 62% between 2002-2011 and they have lost 30% of their geographical range, with African savanna elephants declining by 30% between 2007-2014. This dramatic decline has continued and even accelerated with cumulative losses of up to 90% in some landscapes between 2011 and 2015. Today, the greatest threat to African elephants is wildlife crime, primarily poaching for the illegal ivory trade, while the greatest threat to Asian elephants is habitat loss, which results in human-elephant conflict.
To avoid confrontations and protect their crops, people in Asia have traditionally used several tricks to scare off elephants, like beating drums, firing gunshots into the air, or bursting firecrackers. They also produce high sounds to scare elephants(like yelling, screaming). All these methods can lead both elephants and humans to danger. Trophy hunting is another major threat to this giant.
For saving these largest mammals, we are creating a collar that is completely based on Artificial Intelligence(AI) and the Internet of Things(IoT) which can almost solve the existing threats of elephants. Meet our newly designed open-source collar, Elefante.
- Live tracking of elephants
- Geofenceto determine the natural habitat of elephants
- Predictschances of ivory poaching and trophy hunting
- Detectshuman conflict
- Instantnotifications to forest rangers if any threats are found
- Alertswhenelephants enter into rural areas
Model Training with Edge Impulse
Edge Impulse is the leading development platform for machine learning on edge devices, free for developers, and trusted by enterprises. Here we are using machine learning to build a system that can recognize when a particular sound is happening.
In Ivory poaching and trophy hunting, the poachers use high-caliber rifles to get the job done. So any sort of rifle attacks on elephants can be spotted by classifying this rifle sound. Also, this machine learning model will detect ordinary gun sounds too. When we consider the case of human-elephant conflict, there are a lot of sounds to identify. Whether it can be a sound from the humans itself(like yelling) or any other disturbances created by humans like firecrackers, beating drums, etc. By means of this model, we can only classify sound. So we focus on the sound produced during the conflict. Our machine learning model can classify all of these sounds can detect whether there are chances of ivory poaching, trophy hunting, and human-elephant conflict.
For creating the model you need to sign up for the Edge Impulse. Then create a new project by tapping on the ‘+’ icon on the dashboard.
For generating the model we need a lot of datum. The more data you have the more accurate your model will be. Since the goal is to detect the sound of rifles, firecrackers, humans any other sound created during conflicts. We will also need some background noises of the forest to discriminate between these sounds. Any other sounds apart from this will be considered as noises. Most of the forest noises were recorded by our microphone ” Rode Video Micro “. To get the perfect background sound of the forest we have used fur along with the mic. Also recorded without fur, to get the mixed sound of wind and background sound.
We also downloaded some forest background sounds from native websites. We have collected around twenty audio samples of forest background noises. Then we have collected the sounds of different rifles. For each rifle, the sound is taken in Different Contexts, which means the sound of a rifle from far and close will be slightly different. The close and far shot of the same rifle is collected to improve the accuracy of the model. Then we collected different human sounds produced during a conflict like yelling, screaming, groaning, etc. We also collected the sounds of firecrackers, drum beats, etc to identify the human-elephant conflict.
So our data collection is over. Then we need to upload it to the Edge Impulse studio. For uploading the data just moves on to the Data acquisition tab and just choose a file. Then label it and upload it to the training section.
The Edge Impulse will only accept a
.wav sound file. If you have any other format, just convert it to.wav format with the online converters.
So we uploaded all the data with the four different labels such as Firecrackers, Noise, Human, and Gunfire. We have maintained the same frequency for all audio files(44100 Hz). Try to maintain the same frequency for all files.
You can also collect the data from the specified device by the Edge Impulse studio. When the data has been uploaded, you will see a new line appear under ‘Collected data’. You will also see the waveform of the audio in the ‘RAW DATA’ box. You can use the controls underneath to listen to the audio that was captured.
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