Intelligent sensor network for agricultural sustainability and greenhouse gas detection

Overview

This solution is an intelligent, low-cost electronic nose (E-nose) sensor network designed to accurately detect greenhouse gases (GHG) and other gaseous analytes in agricultural environments. The platform integrates nanoengineered sensing materials, chemiresistive sensor arrays, machine learning and deep learning classifiers, and a custom low-cost embedded system with a graphical user interface. By combining novel materials with selective membranes and smart electronics, the system enables continuous, user-friendly monitoring that supports agricultural sustainability efforts, including emissions tracking, soil and crop health assessment, and environmental compliance.

Technical specifications

Key features:

• Nanoengineered sensing materials including metal oxides, phyllosilicates, transition metal dichalcogenides (TMDCs), metal organic frameworks (MOFs), conducting polymers, and carbon nanomaterials, tuned through composition, dimension, morphology, and crystallinity
• Scalable nanomanufacturing processes designed to reduce production cost and enable high-volume deployment
• Chemiresistive sensor array with variable sensitivities for detecting a broad range of inorganic gases and volatile organic compounds (VOCs)
• Metal organic framework (MOF) membranes with selective permeability to improve discrimination of target gases from background interferents
• High-throughput testing to identify optimal material configurations, minimize material use, and ensure sensor ruggedness and longevity
• Machine learning and deep learning classifiers trained to distinguish GHGs from other background gases and reduce false positives
• Low-cost embedded system with an easy-to-use graphical user interface for field deployment and real-time data interpretation

Technology readiness level

The underlying sensing materials and miniature sensor systems have been demonstrated in laboratory settings, with prior federal funding supporting the foundational work. The current program advances the technology through high-throughput optimization of materials (Aim 2), design and evaluation of smart controlled electronics with a user interface (Aim 3), development of novel classifiers for gas discrimination (Aim 4), and prototype testing and validation in both laboratory and field environments (Aim 5). The platform is positioned at an early-to-mid technology readiness stage, moving from validated laboratory prototypes toward field-ready systems suitable for agricultural deployment and partner-driven pilot trials.