IoT and ML‐based automatic irrigation system for smart agriculture system DOI

E G Anoop,

G. Josemin Bala

Agronomy Journal, Journal Year: 2023, Volume and Issue: 116(3), P. 1187 - 1203

Published: March 25, 2023

Abstract The development of the Internet Things (IoT) and machine learning (ML) technologies has triggered smart agricultural systems. In agriculture, irrigation management plays a major role to reduce water waste. monitoring settings, hardware modules, communication technology, storage systems used in were analyzed determine optimal nature flow. This assessment aims give an overview current state system by taking into account weather soil moisture. paper provides comprehensive review utilization various modules Moreover, that aid data transfer for efficient are reviewed. ML method prediction is also evaluated, as well based like cloud databases store predictive As result, all factors contribute systems’ operation potential future paths improving through IoT.

Language: Английский

A systematic review of IoT technologies and their constituents for smart and sustainable agriculture applications DOI Creative Commons
Vivek Ramakant Pathmudi, Narendra Khatri, Sandeep Kumar

et al.

Scientific African, Journal Year: 2023, Volume and Issue: 19, P. e01577 - e01577

Published: Feb. 4, 2023

Due to the world's rapid population expansion, demand for food is anticipated increase significantly during coming decade. Traditional farming practices cannot meet need crop. Conventional methods use resources like land, water, herbicides, and fertilisers rather inefficiently. When it comes making most effective sustainable of production, automation in agriculture garnering a lot interest. How people machines operate on farms has been changed by integrating Internet Things (IoT) with numerous sensors, controllers, communication protocols. A comprehensive literature review key technologies involved smart agriculture, viz. various standards, IoT based intelligent machinery, were compared presented. These sensors continuously producing significant quantity data agricultural field. transmitted central control unit analysis demands fertiliser, pesticides, etc. The architecture importance analytics IoT, case studies current utilising challenges open issues technology discussed. findings provide support selection specific applications.

Language: Английский

Citations

96
Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey DOI Creative Commons
Md. Najmul Mowla, Neazmul Mowla, A. F. M. Shahen Shah

et al.

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 145813 - 145852

Published: Jan. 1, 2023

The increasing food scarcity necessitates sustainable agriculture achieved through automation to meet the growing demand. Integrating Internet of Things (IoT) and Wireless Sensor Networks (WSNs) is crucial in enhancing production across various agricultural domains, encompassing irrigation, soil moisture monitoring, fertilizer optimization control, early-stage pest crop disease management, energy conservation. application protocols such as ZigBee, WiFi, SigFox, LoRaWAN are commonly employed collect real-time data for monitoring purposes. Embracing advanced technology imperative ensure efficient annual production. Therefore, this study emphasizes a comprehensive, future-oriented approach, delving into IoT-WSNs, wireless network protocols, their applications since 2019. It thoroughly discusses overview IoT WSNs, architectures summarization protocols. Furthermore, addresses recent issues challenges related IoT-WSNs proposes mitigation strategies. provides clear recommendations future, emphasizing integration aiming contribute future development smart systems.

Language: Английский

Citations

62
Recent advances in the use of digital technologies in agri-food processing: A short review DOI Creative Commons
Tétédé Rodrigue Christian Konfo,

Fowe Michelle Carole Djouhou,

Mênouwesso Harold Hounhouigan

et al.

Applied Food Research, Journal Year: 2023, Volume and Issue: 3(2), P. 100329 - 100329

Published: Aug. 2, 2023

This review provides an overview of recent advances in the use digital technologies agri-food processing. With increasing demand for food, industry must produce more food with fewer resources while also addressing sustainability concerns. Digital technologies, such as Internet Things, artificial intelligence, blockchain, and robotics, are transforming way is produced, processed, distributed. These offer several benefits, including increased efficiency, improved product quality safety, reduced waste, environmental sustainability. enable real-time monitoring critical parameters, temperature, pH, moisture, which can help prevent spoilage, reduce ensure that safe high-quality reaches consumers. The covers challenges opportunities wider adoption sector, well potential future developments. has to undergo a revolutionary transformation tackle significant by embracing technologies.

Language: Английский

Citations

50
A comprehensive review on smart and sustainable agriculture using IoT technologies DOI Creative Commons
Vijendra Kumar, Kul Vaibhav Sharma, Naresh Kedam

et al.

Smart Agricultural Technology, Journal Year: 2024, Volume and Issue: 8, P. 100487 - 100487

Published: June 11, 2024

The article provides a comprehensive review of the use Internet Things (IoT) in agriculture, along with its advantages and disadvantages. However, it's important to recognize that IoT holds immense potential for generating new ideas could drive innovations modern agriculture address several challenges faced by farmers today. Applications such as smart irrigation, precision farming, crop soil tracking, greenhouses, supply chain management, livestock monitoring, agricultural drones, pest disease prevention, farm machinery are among areas considered implementation this paper. These innovative solutions have revolutionize farming practices, improve efficiency, reduce resource wastage, ultimately enhance productivity sustainability. analysis examines each application terms utility outlines measures necessary effectiveness. Key considerations include addressing connectivity issues, managing costs, ensuring data security privacy, scaling appropriately, effectively data, promoting awareness adoption tools. Despite these challenges, offers numerous benefits sector. paper underscores importance collaboration farmers, technology companies, academia, policymakers issues fully harness IoT. To achieve goal, ongoing research, development, acceptance IoT-driven essential sustain viable option amidst emerging climate change scarcity.

Language: Английский

Citations

40
Harnessing quantum computing for smart agriculture: Empowering sustainable crop management and yield optimization DOI
Chrysanthos Maraveas, Debanjan Konar,

Dimosthenis K. Michopoulos

et al.

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 218, P. 108680 - 108680

Published: Feb. 10, 2024

Language: Английский

Citations

29
Utilizing Deep Learning and the Internet of Things to Monitor the Health of Aquatic Ecosystems to Conserve Biodiversity DOI Open Access
Bobir Odilov, Askariy Madraimov, Otabek Y. Yusupov

et al.

Natural and Engineering Sciences, Journal Year: 2024, Volume and Issue: 9(1), P. 72 - 83

Published: May 30, 2024

The decline in water conditions contributes to the crisis clean biodiversity. interactions between indicators and correlations among these variables taxonomic groupings are intricate their impact on However, since there just a few kinds of Internet Things (IoT) that accessible purchase, many chemical biological measurements still need laboratory studies. newest progress Deep Learning IoT allows for use this method real-time surveillance quality, therefore contributing preserving This paper presents thorough examination scientific literature about quality factors have significant influence variety freshwater ecosystems. It selected ten most crucial criteria. connections quantifiable valuable aspects assessed using Generalized Regression-based Neural Networks (G-RNN) framework multi-variational polynomial regression framework. These models depend historical data from monitoring quality. projected findings an urbanized river were validated combination traditional field testing, in-lab studies, created IoT-depend condition management system. G-RNN effectively differentiates abnormal increases typical scenarios. assessment coefficients system degree 8 as follows: 0.87, 0.73, 0.89, 0.79 N-O3-N, BO-D5, P-O4, N-H3-N. suggested methods prototypes verified against assess efficacy effectiveness. general was deemed suitable, with forecasting mistakes smaller than 0.3 mg/L. validation offers insights into methods' usage pollutants released observation additional regulating usage, specifically biodiversity preservation.

Language: Английский

Citations

29
Evaluating the Use of Intelligent Irrigation Systems Based on the IoT in Grain Corn Irrigation DOI Open Access
Hooman Sharifnasab, Ali Mahrokh, Hossein Dehghanisanij

et al.

Water, Journal Year: 2023, Volume and Issue: 15(7), P. 1394 - 1394

Published: April 4, 2023

This study was conducted to evaluate the management of smart irrigation in grain maize production (KSC 715 cultivar) at Seed and Plant Improvement Institute (SPII) located Karaj, Iran, year 2020. Irrigation performed based on 40% moisture discharge farm capacity compared with long-term meteorological statistics that have become common field (drip system, type strip, determining time apparent reaction plant). The experimental results showed under conditions management, sensitive phenological stages plant occur earlier, is ready be harvested approximately one month earlier; moreover, 35% water consumption can saved. Water decreased from 8839.5 5675.67 m3/ha; addition, yield productivity decreased. Although stress applied intelligent system completed phenology period faster due earlier harvest, by 35%, reduced. Finally, it seems adjusting drought application more tolerant growth future studies experiments, will possible decrease while increasing physical water.

Language: Английский

Citations

25
Modeling and implementation of a low-cost IoT-smart weather monitoring station and air quality assessment based on fuzzy inference model and MQTT protocol DOI Open Access
Mohamed A. Fahim, Abderrahim El Mhouti, Tarik Boudaa

et al.

Modeling Earth Systems and Environment, Journal Year: 2023, Volume and Issue: 9(4), P. 4085 - 4102

Published: Feb. 6, 2023

Language: Английский

Citations

24
Applications of artificial intelligence (AI) in managing food quality and ensuring global food security DOI Creative Commons
Ali Ikram, Hassan Mehmood,

Muhammad Tayyab Arshad

et al.

CyTA - Journal of Food, Journal Year: 2024, Volume and Issue: 22(1)

Published: Sept. 9, 2024

Language: Английский

Citations

14
A Hybrid LSTM Approach for Irrigation Scheduling in Maize Crop DOI Creative Commons

Konstantinos Dolaptsis,

Xanthoula Eirini Pantazi, Charalampos Paraskevas

et al.

Agriculture, Journal Year: 2024, Volume and Issue: 14(2), P. 210 - 210

Published: Jan. 28, 2024

Irrigation plays a crucial role in maize cultivation, as watering is essential for optimizing crop yield and quality, particularly given maize’s sensitivity to soil moisture variations. In the current study, hybrid Long Short-Term Memory (LSTM) approach presented aiming predict irrigation scheduling fields Bursa, Turkey. A critical aspect of study was use Aquacrop 7.0 model simulate content (MC) data due limitations investigated fields. This simulation model, developed by Food Agriculture Organization (FAO), helped overcome gaps sensor data, enhancing LSTM model’s predictions. The trained tuned using combination soil, weather, satellite-based plant vegetation order reductions. study’s results indicated that supported simulations, effective predicting MC reduction across various time phases growing season, attaining R2 values ranging from 0.8163 0.9181 Field 1 0.7602 0.8417 2, demonstrating potential this precise efficient agricultural practices.

Language: Английский

Citations

10