2026 ASEE Annual Conference & Exposition

Toward Intelligent PlantWall Systems: An Engineering Multidisciplinary Educational Project for Sensor Integration and Automation

Presented at Smart Agriculture and Emerging Technologies in Biological and Agricultural Engineering Division (BAE)

The PlantWall project at Oral Roberts University exemplifies a successful interdisciplinary collaboration between engineering and biology students. Now in its third year, this initiative has evolved from a structural and irrigation design challenge into a platform for advanced experimentation with sensor technology and automation. The project is situated in the Biological Sciences Center and serves as a living lab that merges theoretical instruction with applied research.
In the first year, engineering students focused on the mechanical design of the modular plant wall system, including the structural frame, custom pot holders, and passive irrigation. Biology students selected plant species, developed watering schedules, and addressed pest management. In year two, students enhanced irrigation efficiency and structural durability, and the system was showcased at conferences across the United States, Ukraine, Kazakhstan, China, and Canada. It was recognized as an Outstanding Project in both the School of Engineering (2024) and the Department of Biology (2025).
In its third phase, the project pivots toward full sensor integration and intelligent control. Students will deploy PASCO soil moisture sensors alongside temperature, humidity, and light sensors to enable real-time environmental monitoring. The engineering team will implement embedded systems and write software to process sensor data and control irrigation via a dynamic threshold-based algorithm. The biology team will assist in interpreting sensor feedback in relation to plant health indicators and environmental factors.
To deepen system capabilities, sensor fusion techniques will be introduced to combine readings from multiple sources for more accurate environmental assessments. The project will also pilot the application of machine learning to detect watering patterns, predict irrigation needs, and provide early warnings for pest or nutrient issues. These upgrades are intended not only to improve plant health and sustainability but also to expose students to real-world applications of embedded systems, control theory, and AI in agricultural contexts.
The PlantWall continues to provide a robust experiential learning environment aligned with pedagogical goals in engineering education. Assessment will be conducted through student reflections, team deliverables, and performance-based evaluation of automation subsystems. This ongoing project promotes interdisciplinary communication, hands-on learning, and innovation in sustainable agriculture technologies.

Authors
  1. Rachel L Budavich Oral Roberts University
  2. Dr. Elena Gregg Oral Roberts University [biography]
Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026