Real-time crop monitoring. That's what the GearSense web application does. It tracks crop growth day by day. As a user, you can analyze developments to determine which cultivation strategy you want to implement.
Client: Gearbox Innovations
Tasks: Research, Concepting, Visual Design, Prototype, Developing
GearSense in short
What makes GearSense unique? It's the combination of using image recordings and AI to monitor the product—from A to Z—whether it's a tomato, cucumber, pepper, or even a chrysanthemum, gerbera, or rose. Through images, you can observe day-to-day growth and how the plant behaves in response to changing environmental factors, such as the greenhouse climate and the conditions surrounding the plant.
The plant, fruit, or flower itself acts as the sensor, telling us whether it's growing well, receiving the right amount of water or nutrients, and whether it feels comfortable at the set temperature. It tells us about its own life, allowing us to analyze day by day how its conditions can be further improved.
Measuring equals knowing, and by linking the collected data to your own analysis tools or mapping it to your growth model, you can continuously optimize the development of the plant.
Problem Statement
Growers and cultivators use various tools that generate lots of data for their crops. Currently, they cannot link this data well enough to their crops to achieve optimal growth.
Approach
My process centered on the user, starting with initial research to deeply understand the target group.
- Discovery: I deployed a comprehensive survey to capture insights into their current, analog workflows and identify the essential requirements for a successful digital real-time monitoring tool.
- Foundation: Based on the findings, I synthesized a user persona that served as the primary reference point throughout the subsequent concept and design phases.
- Concept & Design: After defining the core user needs, I established the application concept and designed the wireframes. The web application's main feature is its ability to seamlessly integrate visual data (images) with key performance data to facilitate granular observation of crop behavior.
- Validation & Refinement: The final step involved usability testing with members of the target group. Their feedback directly informed a new, optimized design iteration, ensuring the final product meets their needs.
Result
Ultimately, I delivered a prototype of the web application where the target group can combine images and data. Based on the data and images, the target group can monitor the behavior of their crops themselves. Unfortunately, I cannot show more of the application because it is not yet online.
View the GearSense website
