Design and Implementation of Smart Hydroponics Farming Using IoT‐Based AI Controller with Mobile Application System

Abstract

Hydroponics is the soil less agriculture farming, which consumes less water and other resources as compared to the traditional soil-based agriculture systems. However, monitoring of hydroponics farming is a challenging task due to the simultaneous supervising of numerous parameters, nutrition suggestion, and plant diagnosis system. But the recent technological developments are quite useful to solve these problems by adopting the artificial intelligence-based controlling algorithms in agriculture sector. Therefore, this article focuses on implementation of mobile application integrated artificial intelligence based smart hydroponics expert system, hereafter referred as AI-SHES with Internet of Things (IoT) environment. The proposed AI-SHES with IoT consists of three phases, where the first phase implements hardware environment equipped with real-time sensors such as NPK soil, sunlight, turbidity, pH, temperature, water level, and camera module which are controlled by Raspberry Pi processor. The second phase implements deep learning convolutional neural network (DLCNN) model for best nutrient level prediction and plant disease detection and classification. In third phase, farmers can monitor the sensor data and plant leaf disease status using an Android-based mobile application, which is connected over IoT environment. In this manner, the farmer can continuously track the status of his field using the mobile app. In addition, the proposed AI-SHES also develops the automated mode, which makes the complete environment in automatic control manner and takes the necessary actions in hydroponics field to increase the productivity. The obtained simulation results on disease detection and classification using proposed AI-SHES with IoT disclose superior performance in terms of accuracy, F-measure with 99.29%, and 99.23%, respectively.

Advancing horizons in vegetable cultivation: a journey from ageold practices to high-tech greenhouse cultivation—a review

“…In the realm of vegetable farming, precision technologies, cloud computing, and IoT have been harnessed to enhance crop productivity and optimize resource utilization ( Kaushik, 2021 ). The application of AI and ML in smart agriculture has paved the way for the development of IoT-enabled systems for decision making and control resulting in improved crop management and reduced operational costs ( Ramakrishnam Raju et al., 2022 ). Additionally, the integration of AI and IoT technologies has led to the design and implementation of smart hydroponic farming systems further demonstrating the potential for advanced technologies to enhance agricultural practices ( Ramakrishnam Raju et al., 2022 ).…”

“…The application of AI and ML in smart agriculture has paved the way for the development of IoT-enabled systems for decision making and control resulting in improved crop management and reduced operational costs ( Ramakrishnam Raju et al., 2022 ). Additionally, the integration of AI and IoT technologies has led to the design and implementation of smart hydroponic farming systems further demonstrating the potential for advanced technologies to enhance agricultural practices ( Ramakrishnam Raju et al., 2022 ). The use of robotics in vegetable farming has also been a focal point with robots playing a critical role in preventing future food crises caused by population growth ( Li et al., 2022 ).…”

Implementasi dan Sosialisasi Smart Farming Hidroponik Berbasis Internet of Thing di Dusun Ngentak, Bulakrejo, Sukoharjo

“…Solusi yang ditawarkan untuk mengatasi permasalahan mitra berupa implementasi dan sosialisasi smart farming hidroponik berbasis internet of thing (IoT). Penerapan IoT akan memudahan dalam monitoring dan pengaturan otomatis kebun hidroponik sehingga mengoptimalkan panen (Aliac & Maravillas, 2018;Katti et al, 2020;Ramakrishnam Raju et al, 2022;Razif et al, 2020;Sudharsan et al, 2019;Wedashwara et al, 2021).…”

Research on the evaluation method of agricultural intelligent robot design solutions

“…Wongchai Anupong et al [ 4 ] proposed a new technique of integrating soft measurement techniques for remote sensing models based on the intelligent sensing function of AI sensors to improve the accuracy of information collected in agriculture. Ramakrishnam Raju S. V. S et al [ 5 ] studied how to develop hydroponic agriculture using IoT and sensor technology. Firstly, real-time sensors, NPK soil, sunlight, turbidity, pH, temperature and camera modules were installed.…”