Inspiration

HiKisan is inspired by the daily struggles and aspirations of farmers. The desire to create a platform that simplifies their tasks, enhances productivity, and ensures better crop health serves as a driving force and aids them in their every aspect of Work.

What it does

HiKisan India utilizes TensorFlow Lite for AI-powered disease detection and crop recommendation. The app allows farmers to capture crop leaf photos, which are analyzed for diseases. A voice assistant facilitates hands-free interaction, and multilingual support enhances accessibility, making it a comprehensive tool for efficient and user-friendly agricultural management.

How we built it

We developed the HiKisan India app using Kotlin for Android development and integrated TensorFlow Lite for AI-driven disease detection and crop recommendation. The app enables farmers to capture crop leaf photos, analyzed by TensorFlow Lite for disease detection. Additionally, a voice assistant facilitates hands-free interaction. The app, currently supporting languages like Hindi and Marathi, aims to provide comprehensive agricultural support.

Challenges we ran into

Challenges included optimizing TensorFlow Lite for efficient mobile use and fine-tuning multilingual support, along with that brainstorming was also a task.

Accomplishments that we're proud of

Key accomplishments we're proud of include successfully implementing AI-driven disease detection and crop recommendation in the HiKisan India app, overcoming challenges in optimizing TensorFlow Lite, and delivering a feature-rich, multilingual platform for enhanced agricultural support.

What we learned

In the process of developing HiKisan India, we gained valuable insights into optimizing AI models for mobile applications, implementing multilingual support effectively, and overcoming technical challenges collaboratively. We also deepened our understanding of agricultural needs and the potential of technology to address them.

What's next for HiKisan

Future advancements in HiKisan include incorporating a one-on-one user interaction with an expert and developing a price prediction model for crops the farmers are planting.

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