Sustainable Automated Vertical Farming

This study offers a thorough strategy for automated vertical farming that is sustainable in response to the urgent problems that traditional agricultural methods are currently facing. The primary objective is to design and implement a real-time monitoring and alert system which is capable of optimizing growing conditions and ensuring the long-term viability of vertical farming operations. The system architecture revolves around the integration of sensor technology, automation, and data analytics to enable proactive management of environmental parameters crucial for plant growth. Specifically, sensors are connected to a microcontroller to capture data on temperature, humidity, motion, light intensity, fire state, air quality, and soil moisture. This data is continuously monitored and analyzed in real-time to detect anomalies and deviations from optimal conditions. Upon detecting abnormal conditions such as low light intensity, fire risks, low soil moisture, or unstable rack conditions, the system triggers alerts via SMS using the Twilio service. These alerts are sent to some designated recipients, allowing for timely interventions to rectify the situation and prevent potential crop loss. The proposed system aims to address key gaps and areas of improvement in current vertical farming practices. The results or potential benefits involve reduction in energy costs and water usage based on analytic report custom to farmer, reducing operational expenses and trade it with one-time capital expense by means of reduction in labor costs cut by 40-60% (estimated) and further help to avoid skill issue concern of the labors. The crop production process is made more efficient and optimized with precise use of natural resources which in-turn makes the system more sustainable and improves crop yield and quality. The process gets automated by using actuators which rectify or act on emergency alerts instantly, therefore increasing reliability and propose customization to the customer. By providing a proactive approach to environmental management, it seeks to enhance resource efficiency, crop quality, and overall productivity. Moreover, by leveraging advanced data analytics techniques, the system offers insights into environmental trends and patterns, enabling informed decision-making and adaptive responses. Overall, the system represents a significant step towards the realization of sustainable automated vertical farming. By harnessing the power of sensor technology, automation, and data analytics, it offers a scalable and efficient solution to the challenges facing modern agriculture. It can fully realize vertical farming's potential as a resilient and sustainable food production system for the future use.