Optimal Proportional Integral Derivative (PID) Controller Design for Smart Irrigation Mobile Robot with Soil Moisture Sensor

Azar, Ahmad Taher; Ammar, Hossam Hassan; Silva, Gabriel De Brito; Razali, Mohd Saiful Akmal Bin

doi:10.1007/978-3-030-14118-9_35

Cited by 10 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Major progress has been made toward soil mass transport and fate modeling, including watershed-scale models, single phase flow models and poly scale scape models, which effectively explicate complex soil dynamics. , Detailed soil information from these models can be organized, harmonized, and visualized by DSM. Furthermore, current environmental and agricultural control strategies highly rely on the data-based controller (e.g., proportional integral derivative (PID) controller and supervisory control and data acquisition (SCADA) controller) to provide optimal management strategies. , However, owing to the lack of continuous soil physical/chemical/biological information, these models and control strategies remain disjointed between soil abiotic and biotic processes . Thereby, various types of RTCSM are expected to provide comprehensive, first-hand, continuous and high-resolution soil data sets, decode the “black box” of heterogeneous soil environment, and ensure self-parameter tuning for efficient environmental and agricultural practices.…”

Section: Current State and Challenges Of Rtcsm Data Application In So...mentioning

confidence: 99%

A Critical Review for Real-Time Continuous Soil Monitoring: Advantages, Challenges, and Perspectives

Fan

Wang

Funk

et al. 2022

Environ. Sci. Technol.

View full text Add to dashboard Cite

Most soil quality measurements have been limited to laboratory-based methods that suffer from time delay, high cost, intensive labor requirement, discrete data collection, and tedious sample pretreatment. Real-time continuous soil monitoring (RTCSM) possesses a great potential to revolutionize field measurements by providing first-hand information for continuously tracking variations of heterogeneous soil parameters and diverse pollutants in a timely manner and thus enable constant updates essential for system control and decision-making. Through a systematic literature search and comprehensive analysis of state-of-the-art RTCSM technologies, extensive discussion of their vital hurdles, and sharing of our future perspectives, this critical review bridges the knowledge gap of spatiotemporal uninterrupted soil monitoring and soil management execution. First, the barriers for reliable RTCSM data acquisition are elucidated by examining typical soil monitoring techniques (e.g., electrochemical and spectroscopic sensors). Next, the prevailing challenges of the RTCSM sensor network, data transmission, data processing, and personalized data management are comprehensively discussed. Furthermore, this review explores RTCSM data application for updating diverse strategies including high-fidelity soil process models, control methodologies, digital soil mapping, soil degradation, food security, and climate change mitigation. Finally, the significance of RTCSM implementation in agricultural and environmental fields is underscored through illuminating future directions and perspectives in this systematic review.

show abstract

Section: Current State and Challenges Of Rtcsm Data Application In So...mentioning

confidence: 99%

A Critical Review for Real-Time Continuous Soil Monitoring: Advantages, Challenges, and Perspectives

Fan

Wang

Funk

et al. 2022

Environ. Sci. Technol.

View full text Add to dashboard Cite

show abstract

“…By adjusting panel positions without additional hardware, their approach enhanced energy output efficiency, particularly during cloudy conditions, leading to a remarkable 15.85% increase in output power in fixed array mode. Azar et al (2020) proposed the development of a prototypic mobile robot for smart irrigation to address the challenges posed by weather uncertainty in the agricultural industry. The smart irrigation system the offered utilizes a soil moisture sensor to measure soil moisture content and automatically activates the water pump when necessary.…”

Section: Robot-based Smart Irrigation Systemsmentioning

confidence: 99%

New Trends in Computer Sciences

View full text Add to dashboard Cite

Agriculture plays a crucial role in driving economic growth worldwide. With the continuous growth of the global population, the need for food production and labor has become increasingly demanding. However, agriculture faces various challenges throughout the entire process, from planting to harvesting. Key obstacles include inadequate chemical application, pest and disease infestation, improper irrigation, and drainage, weed control, and yield forecasting. These challenges have sparked discussions and concerns about automating agricultural practices. The advent of artificial intelligence (AI) has brought about significant changes in the field of agriculture. This transformative technology offers solutions to safeguard agricultural production against threats such as population growth, climate change, labor disputes, and food security concerns. By harnessing sensors and incorporating them into robots and drones, AI can assist with irrigation, crop monitoring and other vital agricultural tasks. This not only improves worker safety but also mitigates the impact on natural ecosystems, enabling the maintenance of affordable food prices while ensuring increased food production to meet the needs of our expanding global population. This proposed study is designed to highlight the paradigm shift taking place in agriculture, placing a strong emphasis on the integration of AI-driven robots and drones in cultivation, irrigation and crop monitoring. It underscores the tremendous potential of these evolving technologies to address the global challenges associated with feeding a growing population while simultaneously promoting sustainable farming practices. By leveraging AI, robotic farming offers a promising future where agricultural processes are more efficient, productive, and environmentally friendly.

show abstract

Optimal Design of PID Controller for 2-DOF Drawing Robot Using Bat-Inspired Algorithm

Azar

Ammar

Beb

et al. 2019

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Optimal Proportional Integral Derivative (PID) Controller Design for Smart Irrigation Mobile Robot with Soil Moisture Sensor

Cited by 10 publications

References 8 publications

A Critical Review for Real-Time Continuous Soil Monitoring: Advantages, Challenges, and Perspectives

A Critical Review for Real-Time Continuous Soil Monitoring: Advantages, Challenges, and Perspectives

New Trends in Computer Sciences

Optimal Design of PID Controller for 2-DOF Drawing Robot Using Bat-Inspired Algorithm

Contact Info

Product

Resources

About