Project summary

Seaweed farming is one of the most promising frontiers for marine biomass production and coastal economic development. It is emerging as one of India's most promising blue-economy opportunities. In India, this cultivations happens on a huge scale at Andaman & Nicobar Islands, where over 40,000 farmers are entering the sector. The govt. has been investing a huge deal of money into this sector recently...Despite of initiatives worth roughly ₹640 crore rolling out, most of the work in this sector is still manual ie. monitoring is done from row boats (regardless the tide condition & weather), zone identification is very manual and time taking. Whatever infrastructure we've is very expensive as salt water corrodes most conventional hardware.

Our project, The Seaweed Monitoring Buoy is an autonomous, marine-grade "robot" that makes life easier !  A fleet of buoys equipped with sensors and cameras collects data continuously from it's environment and inputs it to our propriety AI model - The Soloman Model - to generate geographic suitability and health maps for farming zones. Once these areas are identified, the same fleet on the users command will carry out the agricultural process, right from sowing to monitoring to harvesting over the span of next 4-6 months.

Our current prototype demonstrates the core capabilities, but lacks the marine grade hardware and the proper robustness to survive the sea. This proposal requests $20,000 to complete the above mentioned prototype.

1 min video summary : https://youtu.be/r7W554NqQGc?feature=shared

Goals

The utilization of $20k is around the development of the core features of the buoy - Zone Scanning, Automated Planting, Continuous Monitoring, Automated Harvesting and Marine-Grade Durability. The amount will be invested in development of a proper sturdy model intended to validated in real environments - the sea ! Our goal is to make a working model, harvest some good seaweed biomass and licensing of the underlying ocean and growth database to interested parties (R&D institutes, marine-product companies, and government agencies).

What'd the Buoy be able to do finally :

1. A unit or fleet of buoys goes on a data-collection "tour" of the target ocean area.

2. Onboard sensors and cameras record environmental and visual data as the buoy moves.

3. Collected data is filtered and processed at the edge before transmission.

4. The processed dataset feeds the Soloman AI model, which produces a geographic map classifying ocean zones by farming suitability, including heatmaps and other growth-relevant parameters.

5. That map is fed back into the autonomous fleet, which executes planting, monitoring, and harvesting.

6. All data and operations sync to the cloud and connected platforms for remote oversight.

How will this funding be used?

We've a rough estimate of where we'd use the $20,000 :

1. Hardware modeling (fabrication & mechanical reinforcements) - ~$3,000

2. Electronics (PCB design, microcontrollers, motors, etc.) - ~$2,000

3. Rental GPU (sensor data processing & map generation) - ~$1,200

4. Logistics (boat trips to deployment site) - ~$1,800

5. Sensors & cameras (marine-grade) - ~$6,500

6. Power & energy system (marine-compatible batteries) - ~$1,800

7. Anchoring system (else it crashes & sinks) - ~$1,500

8. Connectivity (satellite messaging, >5 km offshore) - ~$1,200

Team

It's the 3 of us working on The Seaweed Monitoring Buoy project - Ankush Das, Adarsh Soloman (yes, as in the AI model) & Samarth Nadig. I've had some good experience with govt. bodies and have received awards from them for my innovations. Adarsh is the AI guy who has expertise in NLP & LLM and has founded Vysan (CTO), Addon (CTO), Isomorph (lead research). Samarth is the hardware expert, versed in edge devices (jetson series of Nvidia), having 2 major publications in the same domain.

Risk factors and Risk Mitigation

With reference to our planning and experience, we've identified 4 spots where everything could go south. In case if any of them hit us, we've developed some strategies to tackle the problem.

1. Risk: Ocean conditions prevent reliable testing

Solution : Sea can be rough sometimes, and as the near-term goal is proving the unit as a reliable data-collection platform rather than a permanent offshore installation, we can carry out testing in calmer, controlled environments such as a river or swimming pool.

2. Risk: Logistics and shipment delays

Solution : Supply run - Kolkata ! It's he nearest major-city harbor. We'd prefer buying components in bulk and transporting them as inventory rather than island shipments.

3. Risk: Corrosion and component failure in marine conditions

Solution : A proper metal choice (316L stainless steel) and a better hardware choice.

4. Risk: Underfunding relative to the full $20,000 ask

Solution : The budget is structured so that a partial raise (down to the $10,000 floor) still funds a complete, testable unit. The testing-iteration budget being the first line item scaled back.