Airable Inc.
Airable Inc. is a drone-based startup that aims to supervise farm cattle and diagnose its illness using Artificial Intelligence.
The specific problem we are trying to solve is the late and inaccurate detection and diagnosis, and inefficient monitoring of animal diseases in farm cattle. The scale of this problem is significant, as it affects not only the cattle industry but also the safety and quality of meat and dairy products for human consumption. According to the World Health Organization (WHO), food-borne illnesses caused by bacterial and viral pathogens present in meat and dairy products affect 600 million people globally every year, and these numbers are on the rise. In the United States alone, according to the Centers for Disease Control and Prevention (CDC), there are an estimated 48 million cases of foodborne illnesses annually, resulting in around 128,000 hospitalizations and 3,000 deaths. Additionally, according to the USDA, diseases such as bovine tuberculosis and brucellosis cause millions of dollars in losses for the US cattle industry each year, with bovine tuberculosis alone causing an estimated $100 million in losses annually.
Furthermore, the problem is exacerbated by the increasing number of farm animals, with the global cattle population estimated to be around 1.5 billion, and the inability to supervise them all at once. This makes it difficult for farmers to detect and diagnose illnesses promptly, which allows the disease to spread and cause significant losses. The National Agricultural Statistics Service (NASS) reports that in the United States alone, 20 million chickens, 387,000 cattle, and 166,000 pigs have died from disease.
The consequences of this problem are far-reaching. The deaths of farm animals not only cause financial losses for farmers and big farming companies, but they also affect the quality and safety of meat and dairy products for consumers. Additionally, not recognizing the nature of the disease can cause many problems, starting with the distortion of the animal, and since we consume farm animals, even a small illness can affect human health.
Our solution is a drone-based system that aims to detect and diagnose illnesses in farm cattle at an early stage. The system uses advanced technology to scan and analyze images of cattle, in order to identify any signs of illness. The system is designed to be easy to use for farmers and is able to detect and diagnose diseases promptly, which can help to reduce the spread of disease and improve the health of the animals.
When the drone captures images of the cattle, the images are analyzed by the AI algorithms which can detect any abnormalities in the animals' appearance. If a diseased animal is identified, the system will mark it and provide the farmer with the location of the animal, so that it can be isolated and treated.
This solution addresses the issue of disease-related deaths in cattle, which has increased rapidly in recent years. It also helps to ensure the quality and safety of meat and dairy products for consumers and helps to protect animal welfare. The system is designed to be efficient, accurate, and easy to use, which makes it an innovative solution in the industry. With this solution, farmers can detect and diagnose diseases promptly, which can help to reduce the spread of disease and improve the health of the animals, which in turn will have a significant impact on the industry and help to improve the lives of farmers and big farming companies.
Our solution primarily serves farmers and big farming companies who raise cattle for meat and dairy production. The system aims to directly and meaningfully improve their lives by helping them to improve the health of their cattle, reduce costs associated with caring for the animals, and prevent the spread of disease.
Currently, farmers and big farming companies face various challenges in terms of disease detection and treatment in their cattle. According to the USDA, in the United States alone, diseases in cattle result in an estimated loss of over $1 billion annually. This includes losses from decreased productivity, treatment costs, and death loss. Additionally, traditional methods of disease detection, such as physical examination, can be time-consuming, costly, and may not always detect illnesses in the early stages.
Our solution addresses these issues by using AI and computer vision to detect illnesses early on, allowing farmers and big farming companies to isolate and treat affected animals before the illness spreads. This can lead to a significant reduction in the costs associated with caring for sick animals and lost income from animals that die or are unable to be sold. Additionally, by detecting illnesses in an early stage, the solution also helps to protect consumers from getting infected by consuming diseased animal flesh, and also helps to save animal lives which is beneficial for the company's reputation and for animal welfare. It also provides a more efficient method for disease detection than traditional methods, which can save time
Overall, our solution can help farmers and big farming companies to reduce costs, improve animal health, and prevent the spread of disease, which can lead to a more profitable and sustainable industry.
Our team is well-positioned to deliver this solution because of our skills, background, and experiences in the relevant fields. We have a passion for technology and a desire to make a positive impact. Our combined interests in electrical engineering and artificial intelligence give us the knowledge and skills to work on the hardware and software aspects of the project respectively.
My partner's experience in the TechGirls Exchange Program has given him a deeper understanding of the electronics field and has helped him gain valuable skills such as leadership and teamwork. My experience in AI-related projects and winning a Gold medal and "best delegation" award at Expo Science Asia in Dubai gives me a strong background in the field of AI which is crucial for the success of the project.
Our passion for technology and desire to make a positive impact in our community gives us the drive to deliver this solution and solve the problem of disease-related deaths in cattle.
As a team, we have taken several steps to understand the needs of the population we want to serve, which includes farmers and big farming companies who raise cattle for meat and dairy production.
First, we conducted market research to understand the current solutions available in the industry and identify the gaps in the market. Through this research, we discovered that there were limited options for early detection and diagnosis of diseases in farm cattle, and that most solutions focused on monitoring the animals rather than detecting and diagnosing illnesses.
Second, we reached out to potential users, including local and international farmers, to gather their insights and feedback on the problem. Through these conversations, we were able to understand the challenges they face in detecting and diagnosing illnesses in their animals, and the impact that these diseases have on their operations and the quality of their products.
Finally, we engaged potential users in the design and development of our solution. By incorporating their feedback and input into the design of our system, we were able to ensure that our solution addresses the specific needs of the population we are trying to serve.
Overall, our research and engagement with potential users have helped us to gain a deep understanding of the needs of the population we want to serve and develop a solution that addresses their specific challenges and needs.
- Other: Addressing an unmet social, environmental, or economic need not covered in the four dimensions above.
- Concept: An idea being explored for its feasibility to build a product, service, or business model based on that idea.
Our solution is innovative for several reasons:
Use of AI and computer vision: By using AI and computer vision, our solution is able to detect illnesses in cattle in an early stage, which traditional methods may not be able to do as effectively. This allows farmers and big farming companies to isolate and treat affected animals before the illness spreads, reducing costs and preventing the spread of disease.
Drone-based system: The use of drones allows the solution to cover a large area and inspect multiple animals at the same time, making it more efficient and cost-effective compared to traditional methods of disease detection.
Real-time monitoring: The system provides real-time monitoring of the animals, which means that farmers and big farming companies can quickly respond to any issues that are detected, improving the health of the cattle and reducing losses.
Cost-effective: The solution is cost-effective as it can help farmers and big farming companies reduce costs associated with caring for sick animals and lost income from animals that die or are unable to be sold.
Impact on animal welfare and public health: By detecting illnesses in an early stage, the solution can help to save animal lives and protect consumers from getting infected by consuming diseased animal flesh.
Technical Innovations: The solution uses advanced computer vision and artificial intelligence algorithms, which can detect a wide range of diseases, identify specific symptoms and provide accurate diagnosis. The system also uses drones to cover a large area, inspect multiple animals at the same time and provide real-time monitoring.
We expect our solution to change the market and enable broader positive impacts by making the process of disease detection and treatment in cattle more efficient, cost-effective, and accurate. It can help farmers and big farming companies to improve the health of their cattle, reduce costs, and prevent the spread of disease, which can lead to a more profitable and sustainable industry. The technology can also be used in other animal farming industry and can have a positive impact on animal welfare and public health.
Our impact goal for the next year is to improve the health of cattle and reduce the spread of disease in the agricultural industry. We plan to achieve this goal by launching our innovative solution, which uses AI and computer vision to detect and diagnose illnesses in cattle at an early stage.
To achieve this goal, we plan to take the following steps:
1- Develop a prototype of our solution: This will involve building a drone equipped with a camera and AI algorithms to detect and diagnose illnesses in cattle.
2- Test the prototype: We will test the prototype on a small scale to ensure that it is accurate and effective in detecting and diagnosing illnesses in cattle.
3- Expand our team: We will hire additional engineers to help us improve the accuracy of our solution and develop it further.
4- Secure funding: We will seek funding from various sources such as grants, investors, and crowdfunding to help us cover the costs of development, testing, and launch.
5- Partner with farmers and big farming companies: We will partner with farmers and big farming companies to test our solution on a larger scale and gather feedback.
6- Launch the solution: Once we have ensured that our solution is accurate, effective, and ready for launch, we will make it available to farmers and big farming companies.
We believe that by achieving these steps we will be able to deliver our solution and have a meaningful impact on the agricultural industry.
The AI algorithms used in the solution are based on machine learning, specifically convolutional neural networks (CNNs) and deep learning techniques. These algorithms are trained on a large dataset of images of healthy and diseased cattle, which allows them to learn to detect and diagnose illnesses in new images. The system uses transfer learning, which enables the AI algorithms to be quickly retrained on new data, which allows the system to adapt to new diseases and new conditions.
Once the images are captured by the drone, they are transferred to the AI algorithm for analysis. The AI algorithm then runs the image through a series of convolutional and pooling layers to extract relevant features from the image. These features are then passed through a series of fully connected layers, which are used to classify the image as healthy or diseased. The AI algorithm then produces a probability score for each class, which is used to determine the final diagnosis.
The computer vision component of the solution allows the drones to capture high-resolution images of the animals. The drones are equipped with cameras that can capture images from different angles and in different lighting conditions, which allows the system to detect illnesses that may not be visible to the naked eye. This is particularly useful for detecting subtle changes in the animal's eyes, nose, or mouth, which can indicate a specific illness.
Once the images are captured, they are transferred to the AI algorithm for analysis. The AI algorithm then runs the image through a series of convolutional and pooling layers to extract relevant features from the image. These features are then passed through a series of fully connected layers, which are used to classify the image as healthy or diseased. The AI algorithm then produces a probability score for each class, which is used to determine the final diagnosis.
The system also provides real-time monitoring, which allows farmers and big farming companies to quickly respond to any issues that are detected, improving the health of the cattle and reducing losses. The system is designed to be easily integrated into existing farm management systems, which allows farmers and big farming companies to easily monitor the health of their cattle.
Overall, the solution combines various advanced technologies like AI and computer vision with the use of drones to provide an efficient, accurate and cost-effective way of detecting and diagnosing illnesses in cattle, which can have a significant impact on the industry.
- Artificial Intelligence / Machine Learning
- Big Data
- Robotics and Drones
- Software and Mobile Applications
- Tunisia
As the solution is currently in the project stage, it has not yet been launched. Therefore, we do not currently have any data on the number of people we are serving.
In the next year, we aim to serve a significant number of farmers and big farming companies who raise cattle for meat and dairy production. According to data from the USDA, there were over 900,000 cattle farms in the United States alone in 2020. Our solution aims to directly and meaningfully improve the lives of these farmers and big farming companies by helping them to improve the health of their cattle, reduce costs associated with caring for the animals, and prevent the spread of disease. This can be a major problem in the industry, as according to the USDA, diseases such as bovine tuberculosis and brucellosis cause millions of dollars in losses for the US cattle industry each year.
Our solution also aims to improve the quality and safety of meat and dairy products for the consumers. This is important, as according to the World Health Organization, food-borne illnesses caused by bacterial and viral pathogens present in meat and dairy products affect millions of people globally every year.
It's worth mentioning that the number of people we plan to serve in the next year will depend on several factors, such as the availability of funding, partnerships, and market acceptance. However, we are confident that our solution has the potential to serve a large number of farmers and big farming companies, and have a positive impact on the industry.
One of the main barriers we currently face is the legal limitations of using drones in Tunisia. As mentioned before, while technically, you are allowed to fly a drone in Tunisia, doing so would require permission from various authorities such as the Department of Transportation, the Ministry of Equipment and Housing, the Home Office, and the Ministry of National Defense. The process of getting the permit from those authorities is not easy and can be quite time-consuming.
Another barrier we face is the financial aspect of our project. Developing a prototype requires a significant amount of money and resources, which is currently a challenge for us as a group of high school students working on this project alone. We would need to secure funding or find investors to take our project to the next level.
Finally, a third barrier is the technical aspect of our project. While we have a good understanding of the technology and processes involved in our solution, we are a small team, and expanding our team with more engineers and experts would greatly enhance the accuracy and efficiency of our solution.
None at the moment, but we're working on partnering up with some environmental and robotics organizations.
Our path to financial sustainability involves a combination of different revenue streams. Firstly, we plan to seek funding through sustained donations and grants from foundations, organizations, and government agencies that are interested in supporting our work in the agriculture and animal health industry.
Secondly, we plan to sell our solution as a service to farmers and big farming companies, which will be an ongoing revenue stream. Our service will include the provision of our AI-powered solution as well as ongoing technical support and maintenance.
Additionally, we plan to seek investment capital from venture capitalists and angel investors who are interested in investing in our project.
Lastly, we plan to explore partnerships with large technology companies that are interested in licensing our technology for use in their own products and services. We believe that by diversifying our revenue streams, we will be able to achieve financial sustainability in the long term.