Fuzzy Methods in Smart Farming: A Systematic Review DOI
Irawan Widi Widayat, Andi Arniaty Arsyad, Aprinaldi Jasa Mantau

et al.

Informatica, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 37

Published: Jan. 1, 2024

Smart Farming (SF) has garnered interest from computer science researchers for its potential to address challenges in and Precision Agriculture (PA). This systematic review explores the application of Fuzzy Logic (FL) these areas. Using a specific anonymous search method across five scientific web indexing databases, we identified relevant scholarly articles published 2017 2024, assessed through PRISMA methodology. Out 830 selected papers, revealed four gaps using FL manage imprecise data Farming. provides valuable insights into applications areas needing further investigation SF.

Language: Английский

Modeling of Unmanned Aerial Vehicles for Smart Agriculture Systems Using Hybrid Fuzzy PID Controllers DOI Creative Commons
Sairoel Amertet, Girma Gebresenbet,

Hassan M. Alwan

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(8), P. 3458 - 3458

Published: April 19, 2024

Unmanned aerial vehicles have a wide range of uses in the military field, non-combat situations, and civil works. Due to their ease operation, unmanned (UAVs) are highly sought after by farmers considered best agricultural technologies, since different types controller algorithms being integrated into drone systems, making drones most affordable option for smart agriculture sectors. PID controllers among frequently incorporated systems. Although used drones, they some limitations, such as sensitivity noise measurement errors, which can lead instability or oscillations system. On other hand, provide improved accuracy system responses. When using achieve performance system, it is better share advantages with intelligence controllers. One promising fuzzy controller. The aim this study was control quadcopter states (rolling, altitude, airspeed) leveraging technology adding hybrid controls its were mathematically modeled Simulink/MATLAB platform, controlled For validation purposes, compared classically tuned roll, height, airspeed, provided an improvement 41.5%, 11%, 44%, respectively, over Therefore, suits needs compatible

Language: Английский

Citations

9
Collision Avoidance for Wheeled Mobile Robots in Smart Agricultural Systems Using Control Barrier Function Quadratic Programming DOI Creative Commons
Sairoel Amertet, Girma Gebresenbet

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(5), P. 2450 - 2450

Published: Feb. 25, 2025

The primary challenge is to design feedback controls that enable robots autonomously reach predetermined destinations while avoiding collisions with obstacles and other robots. Various control algorithms, such as the barrier function-based quadratic programming (CBF-QP) controller, address collision avoidance problems. Control functions (CBFs) ensure forward invariance, which critical for guaranteeing safety in robotic within agricultural fields. goal of this study enhance mitigation potential smart agriculture systems. entire system was simulated MATLAB/Simulink environment, results demonstrated a 93% improvement steady-state error over rapidly exploring random tree (RRT). These findings indicate proposed controller highly effective

Language: Английский

Citations

0
Zero Trust-based preventative detection of vulnerabilities for IoT-based precision agriculture: a case-study on the mySense platform DOI Open Access
Rafael Ferreira, Telmo Adão, Raul Morais

et al.

Procedia Computer Science, Journal Year: 2025, Volume and Issue: 256, P. 267 - 275

Published: Jan. 1, 2025

Language: Английский

Citations

0
Intelligent and automatic irrigation system based on internet of things using fuzzy control technology DOI Creative Commons
Xinying Liu,

Zhihuan Zhao,

Amin Rezaeipanah

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 25, 2025

Language: Английский

Citations

0
Predicting Sustainable Crop Yields: Deep Learning and Explainable AI Tools DOI Open Access
Ivan Malashin, В С Тынченко, Andrei Gantimurov

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(21), P. 9437 - 9437

Published: Oct. 30, 2024

Optimizing agricultural productivity and promoting sustainability necessitates accurate predictions of crop yields to ensure food security. Various climatic variables are included in the analysis, encompassing type, year, season, specific conditions Indian state during crop’s growing season. Features such as season were one-hot encoded. The primary objective was predict yield using a deep neural network (DNN), with hyperparameters optimized through genetic algorithms (GAs) maximize R2 score. best-performing model, achieved by fine-tuning its hyperparameters, an 0.92, meaning it explains 92% variation yields, indicating high predictive accuracy. DNN models further analyzed explainable AI (XAI) techniques, specifically local interpretable model-agnostic explanations (LIME), elucidate feature importance enhance model interpretability. analysis underscored significant role features crops, leading incorporation additional dataset classify most optimal crops based on more detailed soil climate data. This classification task also executed GA-optimized DNN, aiming results demonstrate effectiveness this approach predicting classifying crops.

Language: Английский

Citations

3
IoT, AI, and Robotics Applications in the Agriculture Sector DOI
Atin Kumar, Nitish Karn,

Himani Sharma

et al.

Advances in business information systems and analytics book series, Journal Year: 2024, Volume and Issue: unknown, P. 243 - 272

Published: June 28, 2024

This chapter explores the transformative impact of internet things (IoT), artificial intelligence (A.I.), and robotics in modern agriculture. By addressing challenges such as climate change, water scarcity, labor shortages, these technologies have revolutionized farming practices, enabling precise monitoring crops, data-driven decision-making, increased operational efficiency. The integration advanced A.I. algorithms robotic systems has led to optimized resource utilization, reduced environmental impact, enhanced sustainable practices. However, cost, data security, adoption barriers must be addressed fully realize potential technologies. also highlights future trends areas for research development, emphasizing further innovation practices agriculture sector.

Language: Английский

Citations

2
Nonlinear Dynamics and Machine Learning for Robotic Control Systems in IoT Applications DOI Creative Commons
Vesna Knights,

Olivera Petrovska,

Jasenka Gajdoš Kljusurić

et al.

Future Internet, Journal Year: 2024, Volume and Issue: 16(12), P. 435 - 435

Published: Nov. 21, 2024

This paper presents a novel approach to robotic control by integrating nonlinear dynamics with machine learning (ML) in an Internet of Things (IoT) framework. study addresses the increasing need for adaptable, real-time systems capable handling complex, dynamic environments and importance learning. The proposed hybrid system is designed 20 degrees freedom (DOFs) platform, combining traditional methods models predict optimize movements. models, including neural networks, are trained using historical data sensor inputs dynamically adjust parameters. Through simulations, demonstrated improved accuracy trajectory tracking adaptability, particularly time-varying environments. results show that strategies significantly enhances robot’s performance real-world scenarios. work offers foundation future research into intelligent systems, broader implications industrial applications where precision adaptability critical.

Language: Английский

Citations

2
Evaluating the Impact of Controlled Ultraviolet Light Intensities on the Growth of Kale Using IoT-Based Systems DOI Creative Commons
Suttipong Klongdee, Paniti Netinant, Meennapa Rukhiran

et al.

IoT, Journal Year: 2024, Volume and Issue: 5(2), P. 449 - 477

Published: June 15, 2024

Incorporating Internet of Things (IoT) technology into indoor kale cultivation holds significant promise for revolutionizing organic farming methodologies. While numerous studies have investigated the impact environmental factors on growth in IoT-based smart agricultural systems, such as temperature, humidity, and nutrient levels, ultraviolet (UV) LED light’s operational efficiencies advantages still need to be explored. This study assessed efficacy 15 UV light-controlling experiments three distinct lighting groups: cultivated using conventional household lights, specialized lights designed plant cultivation, hybrid grow lights. The real-time monitoring light, soil, air conditions, well automated irrigation a water droplet system, was employed throughout experiment. experimental setup conditioning maintained temperatures at constant 26 degrees Celsius over 45-day period. results revealed that combination daylight 4000 K scored highest, indicating optimal conditions. second group exposed warm white red light exhibited slightly lower scores but larger leaf size than third grown under likely attributable reduced intensity or suboptimal levels. highlights potential address challenges posed by urbanization climate change, thereby contributing efforts mitigate carbon emissions enhance food security urban environments. research contributes positioning sustainable superfood optimizing cultivation.

Language: Английский

Citations

1
Optimizing the Performance of a Wheeled Mobile Robot for Use in Agriculture DOI Creative Commons
Sairoel Amertet, Girma Gebresenbet,

Hassan M. Alwan

et al.

IntechOpen eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 29, 2024

Utilizing wheeled mobile robot systems may be essential to solving some of agriculture’s upcoming problems. The present state necessitates the development an adequate controller algorithm due their instability, which calls for a control mechanism enhance stability. As such, much study is needed address this issue. Currently, proportional, integral, derivative (PID) controllers are widely employed purpose; however, because parameter variations or disturbances, PID approach often not acceptable. Some problems with can solved alternative strategies, such as linear-quadratic regulator (LQR) control. For work, four-wheel skid-steering robot’s kinematic model was created in order evaluate performance LQR Three scenarios—only non-zero expensive; expensive, cheap; and cheap, expensive—were analyzed using capabilities robot. Based on these circumstances, peak time, settling rising time cheap were determined 0.1, 7.82, 4.39 s, respectively.

Language: Английский

Citations

0
Fuzzy Methods in Smart Farming: A Systematic Review DOI
Irawan Widi Widayat, Andi Arniaty Arsyad, Aprinaldi Jasa Mantau

et al.

Informatica, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 37

Published: Jan. 1, 2024

Smart Farming (SF) has garnered interest from computer science researchers for its potential to address challenges in and Precision Agriculture (PA). This systematic review explores the application of Fuzzy Logic (FL) these areas. Using a specific anonymous search method across five scientific web indexing databases, we identified relevant scholarly articles published 2017 2024, assessed through PRISMA methodology. Out 830 selected papers, revealed four gaps using FL manage imprecise data Farming. provides valuable insights into applications areas needing further investigation SF.

Language: Английский

Citations

0