Model-Prime Accelerates Four Growers’ Greenhouse Robotics
A company at the forefront of automated greenhouse crop management, Four Growers was founded in 2018 with a mission to revolutionize farming and agriculture. Their autonomous robots navigate greenhouse rows and swiftly select ripe produce for harvest at the right time, reducing labor costs and enabling the supply of healthy, affordable local produce to consumers.
Four Growers robots collect and analyze vast amounts of valuable data daily. Through this data, robot performance is continually improved, and greenhouses can learn about their production enabling them to increase their yields.
The challenge: Overcoming bottlenecks in robot data management
Four Growers robots’ capacity to collect valuable data on crops demands the right technology to process it and engineers to work with it: Going through and analyzing robot logs, retrieving specific information, and performing other crucial data-related tasks are often time-consuming, manual processes. In this case, Four Growers sought a software solution to facilitate data management, which manifested as a development workflow bottleneck.
Struggles with log search and retrieval
The Four Growers engineering team stores robot data logs in the cloud, but native cloud storage search didn’t allow them to easily find the data they needed to support their troubleshooting and development processes. Engineers weren’t able to filter data based on crucial parameters like location, weather conditions, or software version and instead had to search for them manually, looking through folders and comparing timestamps—a tedious process, especially when dealing with an increasing fleet size. Hence, finding robot logs was time-consuming and cumbersome and slowed down tasks like data analysis or troubleshooting.
Limited data analysis and context
After retrieving the logs they needed, Four Growers engineers still had issues extracting meaningful insights from them. While logs can capture valuable sensor data, they need human context for interpretation. Four Growers lacked a system to enrich the collected data with additional insights. Hence, observations during testing or production runs often weren’t captured alongside logs, making it difficult to interpret the data quickly and accurately. As a workaround, engineers relied on manually adding annotations after the data was already in the system. As such, transforming raw data into actionable insights was a time-consuming process and left engineers with little room to track trends and identify performance issues.
Lastly, analyzing the downloaded log files added another layer of complexity. Engineers were forced to download the files and load them individually into a dedicated simulation environment to review information about the logs or to analyze results, consuming valuable engineering time and adding another step to an already inefficient workflow.
The Solution: Model-Prime’s platform saves time and adds depth to log analysis
Model-Prime provided Four Growers with a cloud-based data platform specifically designed to address its data issues. Adopting Model-Prime’s secure and scalable cloud platform allowed Four Growers to unlock a new level of data management and solve the challenges it was facing thanks to a two-pronged solution.
Robot logs annotation and search plugin
To reduce manual efforts to understand and locate relevant log files, Model-Prime provided both an intuitive RQT plugin and a web-based application. Both allow Four Growers engineers to browse through and search a catalog of its log files. This enables the engineers to not only quickly view results from robot runs but also to search based on patterns of interest.
In this case, Model-Prime provided a user-friendly interface so engineers can view their entire log catalog, allowing them to:
- Effortlessly find the right logs: Quickly filter and search based on key parameters like robot type, region, season, and software version instead of tedious folder navigation.
- Implement native annotations: View and add crucial contextual notes made by operators during testing or production runs. No more missing insights due to absent human observations.
- Avoid downloading log files: The ability to browse and analyze log data without the need to download multiple files and individually load them into a simulation environment.
This intuitive system streamlined log search and retrieval, saving Four Growers a staggering 5-10x in time compared to their previous methods. Now, valuable insights are just a click away, critical for faster decision-making.
Model-Prime also provides API access so Four Growers could build a custom application to help monitor performance annotations in the field and write them to the log. This allowed for
Powerful log analysis and insights
Model-Prime also understood Four Growers’ need to transform raw data into actionable knowledge. Their solution included:
- Intelligent log search engine: Analyze groups of logs based on specific patterns and annotations. Need to understand robot behavior under cloudy weather conditions? Simply filter and find all relevant logs with that annotation.
- Effortless performance metrics: Automatically summarize and chart key performance metrics categorized by robot, region, season, and software version. No more manual calculations or lengthy spreadsheets to extract insights from data.
Through Model-Prime’s innovative solutions, Four Growers is able to more efficiently leverage their robot data. With a powerful search and analysis engine, Four Growers can now quickly identify performance issues, track trends, and optimize their robotic solutions to offer a better product to their clients. With newfound efficiency and deeper insights, the company can now focus on what it does best: developing cutting-edge robotics that nourish communities and revolutionize sustainable agriculture.
Impact Summary
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