Automated Vertical Gardening System Using IoT-Enabled Smart Irrigation for Sustainable Urban Green Spaces

Abstract

Urban development has caused significant vegetation loss, leading to air pollution, increased temperatures, and ecological imbalance. Vertical gardening addresses space constraints in cities, but manual maintenance is inefficient and costly. This work presents an IoT-based intelligent vertical garden system using a NodeMCU microcontroller and environmental sensors to continuously monitor plant conditions and automatically control irrigation. A 30-day field study showed 44% water savings, 90% cost reduction, and 98.7% system reliability, making it suitable for residential, commercial, and public spaces. The system is supported by an Android application that enables remote monitoring and control. Users can view real-time soil moisture, temperature, humidity, and pH values, switch between automatic and manual modes, adjust thresholds, and initiate irrigation instantly. The app also provides alerts for low moisture, system failure, or abnormal behavior, ensuring timely intervention. This integrated hardware-software approach makes automated vertical gardening practical for homes, hostels, and small institutions.

Introduction

Summary:

Rapid urbanization has led to significant vegetation loss in cities, resulting in poorer air quality, higher ground temperatures, habitat destruction, and reduced urban well-being. Vertical gardening offers a practical solution by integrating vegetation into building walls, improving air composition, reducing noise, providing thermal insulation, and enhancing mental health. However, irrigation management remains a major challenge due to uneven water distribution, safety risks in maintenance, inconsistent manual watering, plant damage from under- or over-watering, and high labor costs that make large-scale municipal implementation difficult.

Advances in microcontrollers, IoT, and environmental sensors provide opportunities to automate irrigation systems. The research proposes a cost-effective, scalable, and autonomous vertical garden irrigation system that integrates multiple sensors and intelligent decision-making to operate without continuous human involvement.

The literature review examines previous IoT-based irrigation systems:

• ESP32-based reservoir monitoring systems achieved automation but lacked plant-level soil moisture control.

• NodeMCU-based sprinkler systems reduced water usage but were designed for horizontal gardens.

• Fuzzy logic and Telegram-based systems offered advanced multi-parameter control but introduced complexity and higher computational demands.

• Solar-powered IoT systems improved energy independence but increased capital costs.

• Home-scale smart garden systems showed good performance but lacked scalability for municipal use.

Despite progress, several research gaps remain, including long-term seasonal testing, multi-parameter integration (moisture, temperature, pH), municipal scalability, weather forecasting integration, economic feasibility analysis, design parameter effects (orientation and materials), and user-friendly interfaces for non-technical staff.

The aim of the project is to develop a simple, affordable vertical garden system that autonomously determines irrigation timing while allowing easy monitoring and control via an Android app.

Key objectives include:

1. Monitoring soil moisture, temperature, humidity, and pH using low-cost sensors.

2. Automatically controlling irrigation duration and timing based on real-time data.

3. Reducing water usage compared to fixed manual schedules.

The problem statement emphasizes challenges unique to vertical gardens, such as gravity-driven uneven water distribution, varying plant needs, environmental variability, public infrastructure constraints, high maintenance costs, and limitations of existing commercial or hobby systems.

The proposed solution is an automated, scalable irrigation framework designed specifically for vertical gardens. It continuously monitors environmental parameters, makes real-time decisions, minimizes water and labor usage, ensures reliability, and remains affordable and easy to operate across residential, commercial, and municipal installations.

The methodology outlines a structured operational pipeline including:

• User configuration and setup

• Continuous sensor data collection

• Intelligent decision logic

• User interface monitoring

• Physical water delivery

• Continuous adaptive control

• Security and reliability mechanisms

Conclusion

Research presented demonstrates that automated irrigation systems specifically designed for vertical gardens effectively address challenges limiting expansion of urban green infrastructure. Systems deliver substantial practical improvements: water consumption decreases by forty-four percent, operational costs drop by ninety percent, plant health improves, and system reliability approaches ninety-nine percent. These improvements are achieved while maintaining acceptable hardware costs and operational simplicity. Financial analysis demonstrates rapid return on investment with initial costs recovered within one to two months of operation. Implementation at scale will require supportive policy frameworks, training programs for municipal staff, and pilot projects demonstrating feasibility in real urban contexts. Future implementation efforts should prioritize: policy advocacy within municipal governments to establish standards and incentives for vertical green infrastructure deployment, educational programs training municipal staff in system installation and operation, partnerships with building developers to integrate systems into new construction from design phase, pilot projects demonstrating feasibility and cost-effectiveness in high-visibility municipal locations to build community support. Strategic deployment of these systems can transform urban landscapes while maintaining fiscal responsibility and operational efficiency.

References

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Copyright

Copyright © 2026 Dr. Bhagyashree Dharaskar, Chandan Lokhande, Mohit Tembhurne, Kunal Patle, Mohit Goupale, Gaurav Hiwase. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.