DroneCrops

Climate change is among the largest contributors to a higher prevalence of crop diseases and a more frequent occurrence of major pest outbreaks. According to research, crop pests account for around one-sixth of farm productivity losses. A higher incidence of pests and diseases, would require more pesticides, which would in turn increase the risk of hazardous residues in food.

In response, We have developed an algorithm that can be applied to high resolution drone imagery to detect pests and diseases affecting crops at an early stage. Our solution uses machine learning algorithms and allows us to perform data analytics to identify pests and diseases at an early stage, and in response enable the farmers to tackle the problem before damage is incurred. This will significantly reduce food wastage at the production level thus improving the lives of millions of people by contributing to food security.

Pests and diseases affects food and cash crops, causing significant losses to farmers and threatens food security in the country. Infestation by plant pests and diseases has increased dramatically in recent years and globalization, trade and climate change, as well as reduced resilience in production systems due to decades of agricultural intensification, have all played a part. Agriculture is the most important enterprise in Kenya, and the highest contributor to the country's GDP, yet low agricultural productivity due to pests and diseases continues to exacerbate poverty, food insecurity, and malnutrition. 

The inability of farmers to detect pest and diseases at an early stage  before damage occurs results in excessive use of pesticides in a dull effort to curb the spread of these diseases and pests, and this leads to more environmental stains. For instance, it has been reported that, half of the smallholder producers in Kenya use more than three times the prescribed volumes of pesticides. This gives rise to potential health risks to both growers and consumers, and a risk to the environment.

Our solution makes use of machine learning to provide an early detection system for crop pest and diseases before any serious damages are incurred. We are in the process of developing a mobile application with an algorithm that allows the farmers to take pictures of affected crops using their mobile phones and upload them. The image recognition app identifies possible defects through images captured by the user’s smartphone camera. 

For the middle and large scale farmers the use of drones will be  much faster and more efficient since they are able to cover a larger area within a short time .The drones are flown over the  selected area as the reflected light is captured from the selected region of the electromagnetic spectrum by the use of a high resolution multi-spectral camera with special filters. The lenses and filters captures the reflected light which allows us to focus on how the plants reflect parts of the EM spectrum differently.  Stressed plants are able to reflect light differently thus distinguishing them from healthy plants.

Our solution has two sides each of which is tailored for different but specific target. 

The mobile application is been developed specifically for small scale farmers with approximately 0-10 acres and who grow food or cash crops like onions potatoes and vegetables. 

The drone solution targets large (50+ acres) and middle (10-50 acres) farmers growing crops such as coffee, tea, pyrethrum and rice. The needs of these farmers vary from one to the next, however one thing is clear. No farmer enjoys losing their hard cultivated crops to pest and diseases. We have therefore engaged several farmers in interviews to understand how best our solution could be adjusted to fit with their needs. The suggestions and input from farmers have been a key factor in informing how we structure the solution as well as our business and revenue models. 

The needs of farmers which include maximum produce and profits, healthy produce and reduced loses will all be met by our drone and mobile application software at the production level. Our solution will also enable the farmers to spend significantly less time, money and other resources in scouting and identifying pests and disease problems within their farms.

Our solution aligns with  the  challenge as it allows farmers to use farm input such as pesticides and herbicides economically through precision spraying achieved by mapping using our drones. Research shows, approximately 30% of total greenhouse gas emissions are  mainly due to the use of  fertilizers and  pesticides. Secondly we shall be contributing to mitigating food loss at the production level through early detection of crops pests and diseases, thus increasing agricultural production. Our solution targets the small, middle and large scale farmers. For these reasons we contribute to more than one of the dimensions listed above.

For hundreds of years, the primary method of detecting crop pests and diseases was human eyes. For larger fields or farms stretching hundreds or thousands of acres, people would be sent out to scout the fields and this would result in loss of important resources such as time, money and labor, not to mention wrong and late diagnosis that would result in tens of acres being destroyed resulting to loss of food. 

Our solution primarily combines several existing technologies to create a new business model, and the collaboration between these different technologies is what drives our solution.

With our solution, the human eye will be replaced with high resolution cameras mounted on drones that are able to take high precision images in large tracks of lands within minutes reducing the cost, time and effort spent on scouting by humans. This will allow quick and correct diagnosis through machine learning algorithms. 

 The ability of our drones to map out only affected areas will significantly contribute to precision spraying and an overall reduction in greenhouse gas emissions brought about by excessive use of herbicides and pesticides, as well as the environmental strain brought about by the chemicals, thus further saving the farmer from unnecessary use of chemicals in the farm. 

Similarly, small scale farmers will have access to more accurate and real-time diagnosis by the use of our mobile application.

The core technologies used in our solution are;-

Drones-The drones are flown over the  selected area as the reflected light is captured from the selected region of the electromagnetic spectrum by the use of a high resolution multi-spectral camera with special filters. The lenses and filters captures the reflected light which allows us to focus on how the plants reflect parts of the EM spectrum differently.  Stressed plants are able to reflect light differently thus distinguishing them from healthy plants.

Global positioning system (GPS)- This will allow our drones to fly along a specific route or path, and thus allow mapping of the fields. Multiple overlapping photos of the ground below are captured as the drone flies autonomously along a flight path that we specify beforehand. The photos are then transformed into a 2D map that the farmer can  use to make decisions regarding their farms

Big data- is a combination of structured, semi-structured and unstructured data. We are in the process of creating a crop pests and diseases database that will house millions of pictures. This will be used together with machine learning algorithm to make predictive analysis of the infection on the crops

AI/ Machine learning- image data is processed into useful information by  analyzing and comparing the images captured by the drones with existing images in the database. The ML algorithm then makes accurate predictions of possible disease or pest affecting the crops

Drones have been around for decades, yet now more than ever, more people are learning to use this technology for better and more efficient operations.

 The first evidence that this technology works, is a Cape Town-based agri-tech company Aerobotics which combines aerial imagery obtained from satellites and drones with its machine learning algorithms to provide early problem detection services to farmers, helping them monitor their crops, get early warning of potential risks, and optimize yields. It provides farmers with accurate statistics on their trees and vines and allows them to use its management zones to plan planting. It now operates across hundreds of farms in 11 countries throughout the world, including Australia and the United States. 

Empire unmanned located in the USA is another evidence that the technology works. This company uses high resolution drone images, land management and plant health observation, forestry and precision agriculture where they conduct moisture level assessment, soil conditions assessment and prediction of crop health. 

 Aker, based in the USA. it is an on-demand drone flight service that collects high resolution images and perform accurate crop monitoring for diseases and pests. All this companies use almost similar business models and are a proof that the same technology can be applied and work in Kenya

We believe we have much to offer our farmers and the entire community at large. With our drone solutions and mobile application for crop pests and diseases, not only will small middle and large scale farmers benefit, but the entire population will enjoy high quality food and the country will be one step closer to realizing one of the big 4 agenda laid out by the government on food security, as well as a step closer to UNSDG 2 on zero hunger. 

To break down our impact even further, we anticipate our drone scouting solution to positively impact the middle and large scale farmers by reducing the number of laborers required to scout the fields. Secondly, due to mapping capabilities of the drone, stressed regions will be easily visible to the farmers who will be able to make better decisions regarding application of pesticides. This will reduce the overall quantity of chemicals sprayed thereby resulting in less crops and environmental strain. Less labor and controlled chemical application means that the farmer will spend less money on accomplishing these tasks, thereby increasing his profits in the long run. In addition to the long term benefits stated above, farms will be capable of producing better quality and quantity of food contributing to food security in the country. 

Similarly, our easy to use and navigate mobile application will allow small scale farmers to experience fewer cases of false diagnosis which eventually leads to use of the wrong chemicals thereby affecting the total food producing capacity.  Farmers will also be able to spend less on hiring professional agronomists to conduct field scouting in a bid to identify the crop stressors. The long term benefits of this platform will be reduced losses, better quality of crops as well as increased profits for the farmer.

We have validated our market but conducting interviews on 136 farmers  in about 17 counties across the country. Among those interviewed, 50% represented the middle and large scale farmers while the rest were small scale farmers. This solution is currently being deployed in South Africa and the USA.

With our solution being at the product development stage, we do not have paying customers that we are serving as of yet. Nonetheless, our main target customer for our product will be small scale middle and large scale farmers across the country. Farming is the most important economic sector in Kenya, despite less than 8 percent of the land in use for crop and feed production, and less than 20 percent  suitable for cultivation. Kenya is a leading producer of tea and coffee, as well as the third-leading exporter of fresh produce, such as cabbages, onions and mangoes. Small farms grow most of the corn and also produce potatoes, bananas, beans, peas and chilies. We are therefore targeting a total of 100,000 small scale farmers for the mobile application and 5,000 large and middle scale farmers. Once we successfully reach this target within the first year, we hope to further scale our operations and target 1,000,000 small scale farmers and approximately 100,000 large and middle scale farmers. 75% of Kenyans rely on Agriculture as their source of livelihoold, with small scale farmers forming the largest portion. We have targeted a larger group of small scale farmers because the mobile application is expected to be available to them free of charge. That means zero operational fee when using our platform.

Product development and piloting- As an early stage company we have been hit hard by COVID-19 and our development plans have been stalled, and this has prevented us from working within the planned schedule. Nonetheless, over the next several months, we would like to complete the product development and test its market feasibility, as well as land our first paying customers. 

Series A investment- This shall be used to boost our operations and increase the scope of our coverage. To achieve this we plan on bringing in more skilled personnel who will spearhead operations in other parts of the country and the East Africa region at large. 

Scaling- In the next five years we would like to expand into the wider East African Region to serve Tanzania and Uganda. We are targeting 2,000,000 small middle and large scale farmers across the three countries.

Partnerships- Forming the right partnerships across the agricultural value chain will enable us to have a wider impact on more people. Meaningful connections will enable us to form better and stronger connections, and give us resources to better provide our services. We would like to form partnerships with organisations such as FAO and Syngenta. 

Expand operations- other than just being a diagnostic company, we would like, in the next five years to expand our operations and assist farmers in analyzing more farm conditions such as soil moisture, temperature and nutrients level. 

Restrictive Drone laws and regulations- We believe that one of the biggest challenge or barrier we might encounter going forward is the many and tough regulations that have been put in place by the Kenya Commercial Aviation Authority (KCAA) surrounding the use of drones. Although these laws are being adjusted to suit  the needs of the users, a lot more still  needs to be done in terms of creating adoptable policies for drones and their use. This can been attributed to the issue of safety and people's privacy as well as national security. 

Lack of funds- Secondly, drones are very expensive to acquire and thus shortage of funds acts as huge barrier to the implementation of our solution. 

Lack of access to information - The third barrier which we are currently experiencing is difficulty in obtaining information regarding all possible crop pest and diseases images that ought to be incorporated into our algorithm. Nonetheless, we are in communication with various government and private agricultural offices on how they might be of assistance to us in terms of data acquisition. 

Restrictive Drone laws and regulations- We are in constant communication with the ministry of Agriculture, who we hope can intervene and have the drone laws restricting us from flying across certain regions lifted or relaxed. There are also tough policies regarding drone ownership and this makes it harder for farmers to own drones.

Lack of funds- We are constantly in the process of looking for funding opportunities such as grants. in order to raise enough funds, we are also pursuing crowdfunding platforms before we can turn to investors for the series round of investment.

Lack of access to information- To build the largest database platform with every possible pest and diseases, we require vast amounts of data. In order to achieve this, we have approached several institutions such as ICIPE, the ministry or Agriculture and other private organisations. This will give us access to the data we need to build the largest crop pest and disease database.

N/A

full time staff - 3

part time - 2

We believe we are the best team to carry out this solution because of the assorted skills each of us has. As the co-founder of DroneCrops, my background in bio systems and agricultural engineering. Over the years, I have developed a special interest in creating sustainable solutions that would help farmers reduce loss of their produce. As such, having specialized in crop production, I believe I have the knowledge required to take this forward. 

Abdi Adan (co-founder) has specialized in computer programming and software development. He has been able to co-develop several other applications that are currently in the market trial stage. I believe his experience and expertise will be highly relevant and needed as we develop our application. He has been able to lead and direct our team of technicians during the product development stage, and has a degree in computer engineering from University of Nairobi. 

Clinton Sang is a trained economist and has been helping us in the development of a sustainable business model. I believe his skills will be necessary in helping us understand the market from different angles and perspectives to see how best we can leverage it. He has a degree in Economics and statistics from Jomo Kenyatta University of science and technology. Each member of our team has something different to offer and i believe this kind of diversity and commitment will be a key contributing factor to the success of DroneCrops.

Chandaria business innovation and Incubation Center has been the most supporting for us as an early stage business. The center selects the best projects each year from Kenyatta University and incubates them as a way to help them reach the commercialization stage. For the past year we have been in partnership with them where they provide us with office working space, mentor ship as well as financial assistance depending with our needs for a  stake of our company. 

We are also in partnership with the Royal academy of Engineering. Our solution was selected for a lengthy period of professional mentorship with access to  a platform where as innovators we can gain access to different opportunities that would help us grow our businesses such as grants and investment opportunities. It also gives us access to mentorship from professionals at Oxentia-UK and this has been  great opportunity for us to learn of international markets. 

We hope to adopt software as a service whereby our employees shall undergo rigorous training on drone operation as per the Kenyan drone regulations. We shall then deploy them to various regions across the country where they shall be able to offer the service to large and middle scale farmers. 

The mobile application to be used by the small scale farmers shall be freely available to the farmers, and this platform shall be used to generate revenue by running sponsored advertisements. The farmers will be able to download the application  on play store and use it without paying any money for it.

The large and middle scale farmers will be required to pay a monthly subscription which shall ensure continuous monitoring of their fields by our trained professionals. The low monthly subscription fee will allow them to keep using the services as opposed to the costly fees of acquiring an individual drone and a license for its operation. This will serve as an entry barrier for other competitors within the market. Our algorithm is set to be the largest data source for pest and diseases in Kenya meaning that any farmer regardless of the crops he/she cultivates, will be able to use our services.  We believe this will enable our customers to keep using the platform to detect pests and diseases affecting their crops

The main reason behind our application to solve is to get access to a wide range of opportunities for example Networking, funding and partnership opportunities. We believe that our solution can be replicated at the global level and for that to happen we would need to be connected to the bigger players in the market. The earth population is expected to reach 9.7 billion people from the current 7.7 billion in 2050. This means that food production systems will have to factor in the growing population so as to ensure food security. FAO estimates that between 20 and 40 percent of global crop yields are reduced each year due to the damage wrought by plant pests and diseases this is often brought about by a failure to monitor the spread of plant pests and diseases which result in disastrous consequences on agricultural production and food security for millions of poor farmers. For us, Solve will introduce us to the rest of the world and as such, be a bridge for us to reach millions of farmers across the world.

We shall require advice in terms of when and where to scale our solutions in different parts of the world and which revenue/business models will be most suitable for other parts of the world. Secondly, drone regulations vary from country to county, therefore we would welcome expert and legal advice on how these laws and regulations change from country to country, and how we can leverage on countries that have relaxed regulations to make the most impact. For us to have maximum impact with our solution, we shall require funding. We would like to receive support therein in terms of available funding opportunities and connection to the best people/organisations supporting similar solutions. Finally, we are looking for a great team of talented and skilled individuals who have a vast experience in the tech industry, particularly in machine learning and we hope that Solve will be of significant help in this. 

Geodetics Incorporated- This will give us access to GEO-MMS LiDAR Tactical 8 which is a drone mapping system. This will allow our customers to easily map out their entire farms and the affected parts for precision spraying

DJI Technology Co.  An off-the shelf drone suppliers located in China engaged in manufacturing of the aerial photography devices. The Company offers innovative drone and camera technology for agriculture.

Previous Solve members in the AI/ML space. These would provide expertise on the best software to integrate with the DJI drones

Refugees are turning to urban farming to improve food security, nutrition, and self-sufficiency. Dozens of small-scale farmers coming from both refugees and host community have been able to produce significant amounts of food in Dadaab using flood recession on land located near a seasonal water pool in Hagadera refugee camp with minimal support from agencies and are able sell their harvest in the camp markets.

As a response to the challenges of inadequate food, the UN, FAO and World Food Program in conjunction with Turkana County Government introduced the kitchen gardens in 2017 to combat food insecurity and provide an alternative source of livelihood to both hosts and refugees. This project has attracted more that 7000 participants. Just like any other farmer, the refugees crops are prone to attack from pests and diseases, and this affects the quality and quantity of food produced. 

We shall use the Andan price to educate the farmers of simple approaches like our mobile platform in combating and dealing with pest at diseases at an early stage. Farmers trained in the use of simple approaches to their crops can significantly increase their efficiency in the production of kales, potatoes and okra which are the most cultivated crops.

Utilizing AI is an efficient way to conduct or monitor possible defects and nutrient deficiencies in the soil. With the image recognition approach, AI identifies possible defects through images captured by the camera. With the help of Al deep learning application are developed to analyse flora patterns in agriculture. Such AI-enabled applications are supportive in understanding soil defects, plant pests, and diseases.

Furthermore, with our solution, farmers will be able to use AI to manage weeds by implementing computer vision, and machine learning. With the help of the AI, data will be gathered to keep a check on the pests and diseases which will then enable the farmers to spray chemicals on the affected parts only. This will directly reduce the usage of the chemical sprayed an entire field. As a result, AI reduces herbicide usage in the field comparatively the volume of chemicals normally sprayed.

In 2018 the worldwide AI in agriculture market was valued at €545 million and, by 2025, is expected to reach €2.4 billion as more and more smallholder farmers adopt new, data-driven technologies. With the help of data scientists and big tech companies, small-scale farmers around the world are increasingly benefiting from the predictive abilities of AI and machine learning in order to access finance and insurance, predict yields and tackle pests and diseases, to run more profitable and ‘smarter’ sustainable farms. The future of AI in agriculture is way ahead in offering radical transformation with advanced approaches.

We shall use the AI for humanity price in advancing our solution across the country and beyond. Educating the farmers on the importance of using technology driven solutions in increasing their productivity is the first step in ensuring we impact the lives of farmers. The price money shall be directed towards further development as well as the acquisition of drones, licenses and training of drone operators to ensure more farmers benefit from our solution.