Automation & AI for Small-Scale Farm Efficiency: A Farmer-Led Innovation Project

Commodities

• Vegetables: beans, beets, cabbages, carrots, cucurbits, eggplant, greens (leafy), greens (lettuces), peas (culinary), peppers, radishes (culinary), tomatoes

Practices

• Crop Production: application rate management, cropping systems, high tunnels or hoop houses, nutrient management, water management
• Education and Training: demonstration, on-farm/ranch research, workshop
• Energy: energy conservation/efficiency
• Farm Business Management: budgets/cost and returns
• Production Systems: organic agriculture
• Sustainable Communities: quality of life, sustainability measures

Farming is Life, a small-scale diversified, certified organic vegetable farm led by Jody Mendoza and Richy Peña in Winchendon, Massachusetts, proposes a farmer-led applied research and demonstration project to test whether affordable automation and artificial intelligence (AI) tools can make small farms more efficient, resilient, and sustainable. The project will design and pilot FAHM (Farm App, Hub & Manager), a low-cost, locally hosted platform that combines (1) a bundle of simple IoT sensors (weather, soil moisture and temperature, and energy use) with (2) an automation stack for irrigation and ventilation in high tunnels, and (3) a mobile app and AI "farm memory bank" for recordkeeping, reminders, and decision support.

Over two growing seasons, Farming is Life will compare a FAHM-managed high tunnel with a conventionally managed control tunnel, tracking labor hours, environmental conditions, water and energy use, crop performance, and recordkeeping time. The primary technical advisors will support automation and sensor integration, while a NOFA/Mass soil and farm systems advisor will help interpret agronomic impacts and ensure the design is relevant to diversified organic farms. To share results, the team will partner with the Pocasset Pokanoket Land Trust and NOFA/Mass to host at least three bilingual workshops and field days, training a minimum of 30 farmers on practical pathways to adopt monitoring, automation, and AI tools. Outreach products will include a fact sheet, how-to video, and a farmer-facing adoption guide that details costs, barriers, and best practices.

The main objective of this project is to provide a cost-effective, scalable platform that allows smaller farms to access the kinds of tools that currently benefit larger operations. This platform, FAHM, will function first as a crop information management and recordkeeping system and second as an automator of key tasks that support plant and soil health while freeing farmer time. FAHM will be a phone-based Hub (the central communication point for the farm) linking and storing historical data from devices that monitor moisture, weather, airflow, and other conditions. It will support team communication and will act as a "farm manager" by recording activities such as plantings and harvest quantities, supporting compliance and certification. FAHM will also provide reminders and decision support (e.g., prompting row cover before a forecasted freeze or flagging when a greenhouse is likely ready for harvest), helping the team prioritize tasks.

On the automation side, FAHM will integrate an IoT-powered control system that can roll up greenhouse sides for temperature control, activate ventilation systems, and turn on irrigation once moisture thresholds are reached using simple "if this, then that" logic tied to sensor data.

We will accomplish this through the following 4 objectives:

1. Prototype and test an integrated, low-cost farm automation stack tailored to small, diversified farms by setting up a bundle of simple IoT tools (ambient weather, greenhouse/bed moisture and temperature, energy-use monitoring, and storage conditions) that actually talk to each other and generate real-time, farm-level data.

2. Develop and test a FAHM app, workflow, and dashboard that pull together field and greenhouse data and organize it into the formats required for real-time recordkeeping and crop reporting for federal and local agencies.

3. Develop outreach materials (fact sheet, video, and field day curriculum), and share project results with the regional farming community, disseminating a practical guide that identifies barriers, costs, and best practices for small farms implementing automation/AI systems and presenting findings at state or regional conference

4. Train at least 30 farmers through education on automation/AI systems and their applications for diversified farms at a minimum of three workshops and field days