Yantra Learning,First Machine Learning Competition in Nepal: Hackathon Edition

Robotics Association of Nepal (RAN) in association with Fusemachines, Inc., Developers Session [Intel Software Nepal Representative] and Synergy Tech Software and other supporters present Yantra Learning 2017. It is a competition for IT and Engineering students where the participants’ goal is to develop algorithms and software infused with AI and Machine Learning for agricultural disaster response. The main objective of Yantra Learning is to train the Yantra (Machine) so it can predict and alert about the possibility of upcoming natural disasters. Also, the winners of the competition will be enrolled in Fusemachines AI Fellowship.

Encouraging IT & Engineering Students to Develop AI System in agriculture field

The goal of Yantra Learning is to encourage young IT and Engineering students to develop AI system in the field of Agriculture. Gaurav Tripathee, Co-Lead of Yantra Learning says “This is probably one of the first tech-related event in Nepal which focuses on AI and especially ML.” He further states, “With this event, we want to attract young aspiring engineering students towards ML and start to create a pool of Nepali ML experts.”

Two-day Hackathon to Nurture the Ideas

The Two-day (Dec 19-Dec 20) hackathon program was held at Fusemachines Nepal Inc. Hall, Hattisar. Different teams from various engineering colleges pitched their ideas to participate in the overall competition. The teams then worked on their own unique ideas on the main task at hand during the Hackathon. Few mentors including the AI Engineering team of Fusemachines were present to interact with the participating teams. Other mentors included personalities from ICT for Agriculture Nepal and Intel Student Ambassador from Developer Session.

Five Teams Competing in the Finals

1)  Technovate:

Team Members: Anish Shrestha, Leela Dhoj Lama, Mahesh Prajapati
The idea behind invention: Taking past weather parameters and crops production and yield to classify the suitable/fit crop for the coming year using the weather forecast data.

2)  Kath:

Team Members: Saroj Dangol, Ritesh Maharjan, Shraddha Amatya.
The idea behind invention: This idea is related to the artificial environment for growing crops e.g. greenhouse. The system will keep records of past production data and their environments. The system will predict new suitable conditions for increasing productivity using past records. If production is increased using prediction data then it will be stored in the system as the best condition. Using this, the best possible conditions will be known.

3) RARS:

Team Members: Raj Shrestha, Satyarth Upadhyaya, Anish Shrestha, Rajiv Shah
The idea behind invention: Plant diseases have been one of the major problems for farmers. This team has proposed to create a system that will help farmers recognize diseases and implement solutions through smartphones. Farmers will be able to identify diseases by taking a photo of the diseased leaf and uploading the image to their cloud server using the android app which they will develop. The RARA team believes the app will then identify the diseases and suggest some solutions.

4) DataSansar:

Team Members: Binod Jung Bogati, Garima Khakurel, Dipika Rai
The idea behind invention: DataSansar team is working on prediction on Tea and Coffee production based on the data of climate, rainfall etc. The team is hopeful this product will help both the farmers and investors get insights on how/when they should cultivate and invest.

5) AgroBot:

Team Members: Ashish Agarwal, Sushanta Ratna Adhikari
The idea behind invention: The main focus of this team is to increase the productivity of poultry and fishing farmers by guiding them to increase the potential of the marketing of their product.  The team is trying to feed some factors regarding this domain in algorithm tree like pond’s size, altitude, temperature and protein availability plus the number of workers. This algorithm tries to analyze previous production rate and consumption rate to help farmers make the right decision in the marketing sector.

The Final Competition

The organizers are planning to have a few more rounds of hackathons and workshops for the participants to get a chance to understand ML more deeply. A date has not been fixed yet but they are planning to have the final competition before the end of January 2018. The Fusemachines’ AI Teams will also be involved in helping the participants on their projects.

For more details and updates please visit their website.

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