DESIGN PROCESS
Internet of Things (IoT) driven B2C solution for Community Supported Agriculture (CSA)
Farmbot as a Service (FaaS) is an Internet of Things (IoT) driven product-service solution designed for community supported agriculture (CSA) farmers. A three person team who executed a user-centered design process over a period of 5 weeks in achieving this design innovation.
Design Concept
Hansong (IU Sponsored)
Market & Customer Research, Product Concept, Prototyping, Business Model
The unique model of CSA has always created a sense of community between farmers and the CSA consumers. However, CSA farmers now are facing a situation of getting consumed by modern competitors and the CSA model requires design intervention for customer retention, business outreach, enhancing productivity and reducing costs.
The design prompt assigned by the Hansong was to 'Design a solution that helps community supported agriculture (CSA) farmers increase their yield and improve productivity to ensure CSA consumer sustainability'
We did an environmental analysis to deeply analyze the CSA market segment, understand customer behavior and needs, and analyze current trends.
Market ResearchSince our focus was on designing a solution that solves the problems of CSA farmers, we realized that our solution would be ineffective if we didn't consider the customers of the CSA farmers - consumers. Hence our target user consists of a primary user (CSA farmer) and a secondary user (CSA consumer).
We interviewed 3 CSA farmers to understand their pains and objectives. The farmers we spoke to had an average of 6 years experience being in the CSA. We also interviewed 2 CSA consumers to understand their needs and the pains they experience with CSA.
"The end consumer satisfaction with CSA is incomparable to any other mode of farming."
"It gets tiring to manage and effectively deliver to a large pool of consumers!"
"We've become used to the high quality CSA food, that store-bought stuff doesn't suit us."
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"A lot of times, my share of food produce gets delayed from the CSA farmer"
We gathered all our findings and designed user personas, one for each of our target users. Creating personas with the pain points and needs enlisted helped us in staying focused and oriented in designing for our target users.
Creating user personas helped in identifying key design drivers which resolve the pains of CSA farmers, meets their needs and also satisfies Hansong's business objectives. The design drivers informed our ideation process.
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A farming robot that will perform farming activities such as soil monitoring, vegetable picking, weed-removing. It can be customized as per farmercontrolled using a mobile app.
Inclusion of Meal-kits into CSA who will customize, package & deliver the boxes to consumers. Solution includes mobile app for CSA consumers, CSA farmers, and dashboard for farmers
Food Kiosk installation where CSA consumers with excess produce can donate which can be consumed by needy people. Sensors in Kiosks will detect and specify longevity of food
After pitching our design ideas to the client, we discussed the effectiveness and the scalability and finalized our final solution - FarmBot as a Service. Since CSA farmers are concerned about affordability, the FarmBot along with its services will be provided on a monthly subscription basis offering the following value propositions.
1. One solution for multiple expensive farm equipments
2. Reduces labor work & costs
3. Quick detection & fixing of crop issues
4. Precision farming
1. Consistent stream of revenue by leasing contracts from the farmers
2. Additional revenue generated from maintenance costs
3. State of the art product in the agriculture sector
4. Differentiates Hansong from competitors
The FaaS IoT ecosystem comprises of 4 components viz. Farmbot, Farmbot controller app, Hansong's cloud and the Dashboard. Let's dive into the individual components in detail and understand their interconnectivity.
1. Storage unit - storing vegetables & manure
2. Wheels for moving
3. Battery powered (lithium ion)
4. Wireless charging capability
5. GPS - location tracking
6. Video camera - remote visibility of vegetables
7. Wifi - send data, receive commands
1. IR sensor - detecting obstacles
2. Optical crop sensor - evaluating vegetable condition
3. Spray sensor - spraying pesticides
4. Tactile sensors - harvesting/vegetable picking
1. Attachable weed removal accessory along with the FarmBot to remove unwanted weeds.
2. A picking system on the arm to pick the vegetables.
3. Machine learning algorithm to understand ripeness & pick accordingly. Ensures cut is smooth and in the right location.
4. A storage container to store vegetables after picking.
1. Attachable weed removal accessory along with the FarmBot to remove unwanted weeds.
2. Perception system powered by machine learning to capture and analyze plant images in real-time.
3. Once images are processed, Farmbot knows where weeds are takes actions
Once we validated our concept with our target user, we proceeded to refine our concept further and created high-fidelity prototypes. We designed the interface for the FarmBot controller app and the data analytics dashboard. The features and the capabilities of the respective devices are enlisted below
- Enables farmer to control the Farmbot and initiate commands (weed removal, harvesting, etc).
- Farmer can monitor the Farmbot operations and is notified when tasks are completed
- Farmer can also see a compact view of dashboard analytics on the app
- Weather prediction service integration to provide actionable suggestions as per produce
- Data from Farmbot (eg: vegetable ripeness) transmitted to cloud via Wifi.
- Farmers can see the status of vegetables (eg. tomatoes in row 2 will be ripened in a week.)
- Bad weather can be predicted and actionable measures are provided as per vegetable condition (eg: Tornado alert! Tomatoes to be covered).
- Also available on the Farmbot controller app.
Since the world got struck with the pandemic, we couldn't do in-person user testing, and gathered feedback through phone calls. We described our design concept to our target users and proposed the value propositions of our idea. Our users liked the idea and were actually interested in seeing it in reality.
We pitched our final presentation to our client that comprised of market research, customer research, analysis, product-service concept, value propositions, revenue model and the entire business model canvas.
FarmBot is a real-world IoT business solution designed and delivered to our client Hansong. I'd like to thank our Prof. Lou Lenzi for his valuable insights and experience in guiding us throughout the course of our project. I was successful in applying human-centered design principles in designing a product-service design and wrapping a business model around it, with the client appreciating the solution.
This project equipped me with the skills of identifying and leveraging business opportunities, service design, working with business & design constraints, generating business models, interacting and presenting in front of real world clients. I gained immense knowledge and evolved tremendously as a Product Designer.
