Farm in a Box Grow Kit with IOT Case Study

by | Jul 1, 2026 | Case Studies

Farm In A Box (FIAB) Grow Kit: A Cross-Curricular IoT Pilot in a YRDSB Secondary School (2026)

THE CHALLENGE

Secondary school computer science classrooms often struggle to connect abstract programming concepts to tangible, real-world outcomes — and to other departments down the hall. At a York Region District School Board (YRDSB) secondary school, the Computer Studies and Family Studies departments wanted to break out of that silo. After securing a Community Centred Experiential Learning (CCEL) grant to build a vertical garden, the teaching team faced several practical challenges:

How to give students hands-on construction and coding experience without specialized makerspace equipment or recurring consumables.

How to embed Internet of Things (IoT) and networking concepts into ICS4U in a way that meets curriculum expectations while producing something students can actually see and touch.

How to create a genuine cross-curricular workflow where Computer Science students’ work directly feeds another department’s program (in this case, Family Studies cooking courses using the harvested plants).

How to do all of this affordably, within school board procurement rules, and in a way that other YRDSB schools could replicate.

 

THE SOLUTION

STEM Minds partnered with the school to run the Farm In A Box (FIAB) Grow Kit as a pilot project, layering hardware, curriculum, and ongoing classroom support:

Student-Built FIAB Grow Kits: Working in groups, students assembled six FIAB kits made from laser-cut wood boards — no glue or screws required — sourced through Kidder, a YRDSB-approved vendor, at $52 per kit.

Sensor Integration with Micro:bit: STEM Minds provided laser-cut extension flaps and Crowtail Starter Kit sensors for Micro:bit, then guided students through installing and coding the sensors to monitor plant growing conditions inside the box.

Guest Speaker Sessions: STEM Minds team members visited the classroom on multiple occasions, working directly with students on construction, sensor wiring, and coding troubleshooting.

ICS4U LoRa WAN Extension: For senior Computer Science students, STEM Minds extended the project into a full IoT pipeline — a Raspberry Pi node reads sensor data from the

THE OUTCOME

 

The pilot delivered a working cross-curricular IoT learning environment that the teacher now plans to extend into additional courses:

Engaged, Hands-On Learners: Students experienced the full arc of a real-world tech project — from physically assembling hardware, to coding embedded sensors, to deploying a wireless data pipeline.

Genuine Cross-Curricular Collaboration: Computer Studies students monitor sprouts and surface plant data; Family Studies students harvest and cook with the plants — connecting the school’s Eco-Council and the community garden across from the school. Visible Course Promotion: Finished FIAB kits are showcased in the school’s library and atrium, generating word-of-mouth interest in CS and Family Studies electives.

Affordable, Replicable Model: a program accessible through CCEL grants (up to $3,000 per school) and SHSM materials budgets.

Curriculum Reuse: The teacher is reusing the FIAB kits in ICD2O to extend the Micro:bit unit, multiplying the return on the initial investment.

A Roadmap Forward: STEM Minds is now working to lower costs further by developing custom sensor packages and in-house PCBs for the LoRa WAN set, while the teaching team is exploring

The Impact & Results: Cultivating Efficiency and Sustainability

The adoption of AI modelling can bring significant and measurable improvements, transforming various aspects of crop management:

  • Enhanced Accuracy: The system has achieved over 87% accuracy in plant health classification, far surpassing the reliability of manual visual checks.
  • Early Detection & Reduced Loss: The AI’s ability to detect issues like leaf mold at an early stage has demonstrably reduced potential crop loss and significantly improved the quality of care provided to plants.
  • Streamlined Management: AI automates routine plant health checks, providing accurate and tailored recommendations. This saves valuable time, drastically reduces the potential for human error, and facilitates smarter crop planning and decision-making.
  • Empowered Team: The AI system reduces the need for constant manual inspection tasks, allowing farm team members to dedicate more time to strategic decisions and other high-value activities. It also serves as an invaluable tool for users with limited experience in identifying plant diseases, making their work easier and more effective, fostering a more skilled and confident workforce.
  • Sustainable Practices: By catching problems early and offering precise care instructions, the AI directly contributes to more sustainable and environmentally friendly farming. It reduces the need for excess water, fertilizers, or chemicals, leading to less waste and fostering healthier crops with fewer resources.

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