An AI assistant that helps you participate in community farming with ease. It assists you to grow your own food with a story to tell

My Role
  • Conducted UX research including primary (contextural inquires) and secondary research to build empathy with target users, uncover problems and generating insights for problem solution and product design.  

  • Lead the team throughout the whole design process to build the product and verify it through user testing. 

Tools / Duration / Teams

Sketch, Figma, Adobe Suite

Feb. 2019 - May. 2019, 4 months

Jingyi Cheng, Shashank Jain, Elizabeth Moore, Ting Pan, Harika Bommu


There are more and more people pursuing a healthy and eco-friendly lifestyle. City residences are coming to the community to grow plants and farm together on the actual field.  However, their busy schedules in life and unfamiliar in farming have been causing trouble for taking care of the plants.

Living an organic and sustainable life is 
Because farming makes so much fun in this rewarding experience.
But it's also very difficult for general public to pursue

------ Scarlett 

I'm interested in growing my own food, maybe tomato or pepper, but I don't have much time and I don't really know how to take care of them


Problem space

What makes farming so difficult?

The questions need to be answered


Farming is our focus. However, there are many aspects and areas we can design for. To answer the very first question and narrow down our scope, we try to fix the scope for our product by understanding who we are creating the product for and what the product is going to be. We listed down all the possible user groups and activities involved in the farming process.  

We narrowed down to focus on urban farmers who live in the city but want to have the experience of growing their own food. And Community plays an important role in supporting urban farming. In conclusion, our target user is urban farmers who participate in communities and wants to grow their food.

Young urban farmers
who joining community farming

We conducted on-site studies and interviews to understand in depth the process of urban farming and all its aspects, including how technology is being currently used. We went to participate and interview 3 urban farms around Austin, including the University of Texas's own student-run micro-farm. We also interviewed the sustainability coordinator at UT for his perspective.

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Work Artifacts

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User journey story

Jill is a hardworking designer during the weekdays and regular volunteer at an Urban farm on the weekends. She is growing a variety of crops this season. Let us see what Jill's urban farming experience looks like.


Community Volunteer


Ideation and iteration

We conducted an indepth literature review on the capabilities of artificial intelligence and its application in the field of agriculture. To consolidate the data, we listed possibilities where AI can help. We found that AI can help in almost all stages of farming in one way or another, and how we use it to develop our product would depend on further research.

What can AI do?

Literature review on technology possibilities

How might we utilize AI assistant to improve urban farmer's experience without too much interruption?


Experience principle

Our solution


Introducing Farmvision

FarmVision is a smart AI assistant that helps urban farmers by facilitating plant planning, recommending sustainable farming techniquesmonitoring plant development but most importantly it grows a story with your plants

Let's see how Farmvision works!

Jill's new journey as a community volunteer

Gamification of the Farm / Task selection / Notification on plant changes

Jill receives a notification about the status of her plants.

She opens the app, checks on how her plants are doing and is really excited that her lettuce is ready to harvest. And she decides to go to the community farm today and selects tasks she would like to volunteer for, including care for her own plants.


This would also help the farm manager plan and manage better by understanding what tasks have people taken responsibility.

Smart glasses for detection and guidance

Jill puts on FarmVision smart glasses. Glasses are connected to a grid of sensors that collect plant health data to analyze and keep volunteers like Jill updated with required tasks

Personalized assistant on tracking tasks and providing guidance

After identifying the person through voice/retina identification, FarmVision personalizes the experience, and shows the relevant tasks and work.


The smart voice-controlled AI assistant help the volunteers in keeping track of tasks and guide them through the process. 

The involvement of the AI assistant in the process is minimal and can be controlled by the user, as the main focus is the tangible experience of farming and community.

Recognize problems / Provide solutions / build a AR plant image to build affection 

After having completed a few tasks, she notices there is something wrong with her Beet plants. The leaves have some holes in them, which were not there the previous week.

Apart from helping with tasks, using AI and image recognition, FarmVision can also help troubleshoot problems

AR plants for engaging experience / build story with the plants 

She is happy that she was able to cure her plants. While walking around the farm, there are many surprises that delight her.  She loves this new experience of  interacting with plants.

Jill puts down the FarmVision smart glasses and goes home. 

Monitor the field in real time / Connect with friends 

Once Jill returns home, she receives a notification about the status of her plants.

She opens the app, and receives points for all the work she did, and the problems she tackled on the farm.​

Mark progress and achievements / build a personal story

The app also lets her track her journey and adds milestones for every big achievement she has. It also guides her on deciding the next plants she wants to grow.

  • Defining the problem, documenting, and having clear goals matter.

While working on a time-bound problem, and that is always, it is useful to have an idea of the project timeline. Timeline updates according to product evolution, but having an overview in mind gives context to each step. Documenting design decisions help maintain a progressive flow, and journey efficient and fruitful.

  • Understanding the technical constrains is important

Working with AI solutions requires us to pay more attention to viable and feasible solutions. Even for the final design, our design is based on a very high-tech technology, because we are asked to design for the AI technology 5 years later from now. But it is still extremely important to consider technical constraints before start diving deeper into the designs.

I'm happy to chat!


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