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OHH 2020 - Ebola Team 3
- 1. ForestGuard Deforestation Surveillance for Zoonotic Disease Control Ebola Team 3: Alan Ma, Rishabh Sharma, Samyak Shrimali, Dev Udata
- 2. Deaths from Ebola 1.3 million 11,300+ 12+ 90% Ebola Outbreaks Square Kilometers of Deforestation Fatality Rate
- 3. Effects of Deforestation ● Deforestation leads to destruction of animal habitat ● Causes some Zoonotic disease-carrying animals to be closer to human populations ● Leads to outbreaks such as Ebola ● Issue in sub-Saharan African countries such as DRC
- 4. ForestGuard aims to track and protect against deforestation in order to prevent loss of animal habitat, lessening the contact of humans with carriers of Zoonotic diseases (such as Ebola).
- 5. What is ForestGuard? Deforestation Analysis Permit Comparison Policy Machine learning based drone/satellite imaging to identify deforestation based on forest health Web application to track illegal deforestation Fully disclosed policy to prevent future deforestation and Zoonotic diseases
- 6. Deforestation Analysis A deep learning model is trained with 2 sets of images, clear forests and dead forests. Model is implemented to drones/satellites for real- time detection of dead forests. As dead forests are detected the drones/satellites reports this information to central web application.Dataset: http://wildfire.fesb.hr/index.php?option=com_content&view=article &id=49&Itemid=54
- 7. Permit Comparison Red is unpermitted forestry Black is regular forestry Black - Dead forest Gray - Dying forests Red - Sharp decline in forest health Yellow - Moderate change of forest health Green - No change in forest health
- 8. Policy 1. If a region is detected in danger of deforestation, the government will ban permits on this region 2. Our permit comparison website will report illegal deforestation directly to the national government 3. The government will allocate specific funds towards those living on the edges of forests
- 9. Feasibility Integration Government Deforestation Permits Comparison Only current measures for preventing deforestation are government- required permits, but since most deforestation is illegal or from poor villagers in nearby towns, much is unreported + +- -
- 10. Feasibility ● Imaging technology already exists (satellite or drones) ● Such machine learning algorithms already exist ● Very low cost of implementation ○ Majority is software and policy enforcement
Editor's Notes
- Good afternoon everyone. My name is Samyak, my name is Rishabh, my name is Alan, and my name is Dev and our proposal is ForestGuard: deforestation surveillance for zoonotic disease control.
- Dev: So far, there have been over 12 major outbreaks of Ebola in sub-Saharan Africa. There have been over 11,300 deaths from Ebola, and those are just the ones that have been reported. Additionally, Ebola is an extremely lethal disease, with a fatality rate of around 90%. Ebola is a zoonotic disease, which means it starts from the spread of germs between animals and people. Around the world, over 1.3 million square kilometers of forested land has been deforested.
- Dev: Deforestation has been known to have a direct link to exposing human populations to zoonotic disease carrying animals. Losing their habitats, forest animals are much more easily hunted and are extremely cheap to consume as a food source. This relationship can be seen through the 12+ ebola outbreaks in recent years in areas with significant deforestation.
- Dev: To solve this problem we created ForestGuard. Our mission is to track and protect against deforestation in order to prevent loss of animal habitats, lessening the contact of humans with carriers of zoonotic diseases such as Ebola.
- SAM: ForestGuard is made up of 3 distinctive parts. The first being deforestation analysis. Here we will be using a unique deep learning model to identify deforestation based on forest health. Then we have our permit comparison website. Government agencies will be able to view sanctioned deforestation areas compared to the illegal deforestation that isn’t being tracked by them. Finally, we have developed a robust policy to bridge the gap between the governments and their citizens. Our policy proposal will incentivize citizens to procure resources outside of the highly affected forests to prevent any spread of zoonotic diseases.
- SAM: Now let’s take a look at how exactly we going to implement our deforestation analysis tool. First, we will train our deep machine learning model against various images that will be tagged as dead forest or forest that exists, this allows our model to make a clear distinction between forested and deforested lands. An overlay of before and after imaging provides a good comparison. Then this model will be implemented with drones and satellites to detect deforestation in real-time. As deforestation occurs, our website will alert government agencies about environmental damages.
- RISHABH: Not only will the government agencies be notified of deforestation in real-time with our technology, but also will be notified of any unregulated deforestation happening. As you can see in our analysis above, we make a clear distinction between permitted and unpermitted sites of deforestation on our website. Government agencies will be informed in real-time about the unpermitted deforestation happening and be able to take action against it. Above in our website, on the right, there is a map with different colors labelling the health of different forested areas. On the left, there is a map with red territory being unpermitted forestry and black territory with permitted forestry. Thus, the government can [Talk about legends]
- RISHABH: Our third step is our policy. The first part of our policy is that once a region has been detected of being in danger of deforestation with our deep learning imaging system, the government will ban logging and mining permits on this region to prevent further deforestation. The second part of our policy will be that our permit comparison website will report illegal deforestation directly to the national government. This will serve as an incentive to logging and mining companies to only do so in permitted areas. The third part of our policy is government-allocated funds towards the poor living near forested areas. These funds will serve as an incentive for these people to buy safer meat, and they will be educated about the dangers of bush meat. With this policy, deforestation will be greatly reduced, leading to a much less risk of a Zoonotic disease outbreak.
- ALAN: There have been no solutions on the market combining usage of technology and deforestation to mitigate the exposure of populations to zoonotic diseases yet. Current solutions are mainly focused on providing permits so that people are limited from cutting down forests. However, this is not effective as such permits are not well regulated. ForestGuard acts as a notification system warning people at risk to greater limit the amount of human to animal exposure.
- ALAN: ForestGuard is highly feasible as imaging technology and is widely applied to many different fields. Machine learning algorithms on image based data is widely accepted as a consistent method of training and testing identification. Forestguard aims to provide a novel approach of application of machine learning to identify deforestation. There is a very low cost of implementation as the majority of costs are software and policy enforcement. The only costs that arise are from imaging technology which are growing cheaper by the day. As an example, here is an image of us testing our drone over a neighborhood forest.
- ALAN: Our solution upholds the One Health Principle which is about considering environmental health, human health, and animal health all together. Firstly, ForestGuard protects the environment by guarding forests against deforestation. This will create a much more green environment. Secondly, ForestGuard protects animals in these forests by preventing the destruction of their homes. Lastly, ForestGuard protects humans near these forests because there will be less contact with zoonotic-disease carrying animals, leading to less risk of disease. Don’t you want government agencies to help protect their people? Join ForestGuard to make this possible. Thanks for listening.