Smart Agricultural Technology, Journal Year: 2024, Volume and Issue: 8, P. 100512 - 100512
Published: Aug. 1, 2024
Language: Английский
Energy Nexus, Journal Year: 2022, Volume and Issue: 7, P. 100124 - 100124
Published: July 25, 2022
Countries are working into making agriculture more sustainable by integrating different technologies to enhance its operation. Implementing improvements in irrigation systems is crucial for the water-use efficiency and works as a contributor Sustainable Development Goals (SDGs) under United Nations specifically Goal 6 Target 6.4. This paper aims highlight contribution of SMART using Internet Things (IoT) sensory relation SDGs. The study based on qualitative design along with focusing secondary data collection method. Automated essential conservation water, this improvement could have vital role minimizing water usage. Agriculture farming techniques also linked IoT automation, make whole processes much effective efficient. Sensory helped farmers better understand their crops reduced environmental impacts conserve resources. Through these advanced soil weather monitoring takes place efficient management. Irrigation been determined positive toward optimized that use continuous research development which focus enhancing operations cost reduction. Lastly, challenges benefits implementation discussed. review will assist researchers provide an adequate approach would be sufficient carry out related activities.
Language: Английский
Citations
214
Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 373, P. 133753 - 133753
Published: Aug. 28, 2022
Language: Английский
Citations
85
Water, Journal Year: 2022, Volume and Issue: 14(5), P. 719 - 719
Published: Feb. 24, 2022
The increase in population growth and demand is rapidly depleting natural resources. Irrigation plays a vital role the productivity of agriculture, consuming no less than 75% fresh water utilization globally. Irrigation, being largest consumer across globe, needs refinements its process, because it implemented by individuals (farmers), use for irrigation not effective. To enhance management, farmers need to keep track information such as soil type, climatic conditions, available resources, pH, nutrients, moisture make decisions that resolve or prevent agricultural complexity. data-driven technology, requires integration emerging technologies modern methodologies provide solutions complex problems faced agriculture. paper an overview IoT-enabled through which management can be elevated. This presents evolution IoT, factors considered effective irrigation, optimization, how dynamic optimization would help reduce use. also discusses different IoT architecture deployment models, sensors, controllers used agriculture field, cloud platforms prominent tools software scheduling prediction, machine learning neural network models irrigation. Convergence tools, approaches helps development better applications. Access real-time data, weather, plant must enhanced
Language: Английский
Citations
80
Agriculture, Journal Year: 2024, Volume and Issue: 14(7), P. 1141 - 1141
Published: July 14, 2024
Water is considered one of the vital natural resources and factors for performing short- long-term agricultural practices on Earth. Meanwhile, globally, most available freshwater are utilized irrigation purposes in agriculture. Currently, many world regions facing extreme water shortage problems, which can worsen if not managed properly. In literature, numerous methods remedies used to cope with increasing global crises. The use precision water-saving systems (PISs) efficient management under climate change them a highly recommended approach by researchers. It mitigate adverse effects changing help enhance efficiency, crop yield, environmental footprints. Thus, present study aimed comprehensively examine review PISs, focusing their development, implementation, positive impacts sustainable management. addition, we searched literature using different online search engines reviewed summarized main results previously published papers PISs. We discussed traditional method its modernization enhancing PIS monitoring controlling, architecture, data sharing communication technologies, role artificial intelligence water-saving, future prospects PIS. Based brief review, concluded that PISs seems bright, driven need systems, technological advancements, awareness. As scarcity problem intensifies due population growth, poised play critical optimizing modernizing usage, reducing footprints, thus ensuring agriculture development.
Language: Английский
Citations
62
Smart Agricultural Technology, Journal Year: 2023, Volume and Issue: 5, P. 100255 - 100255
Published: May 17, 2023
Future agricultural systems should increase productivity and sustainability of food production supply. For this, integrated efficient capture, management, sharing, use environmental data from multiple sources is essential. However, there are challenges to understand efficiently different types sources, which differ in format time interval. In this regard, the role emerging technologies considered be significant for gathering, analyses use. study, a concept was developed facilitate full integration digital enhance future smart sustainable systems. The has been based on results literature review diverse experiences expertise enabled identification stat-of-the-art technologies, knowledge gaps. features proposed solution include: collection methodologies using tools; platforms handling sharing; application Artificial Intelligent analysis; edge cloud computing; Blockchain, decision support system; governance security system. study identified potential positive implications i.e. implementation could value, farm productivity, effectiveness monitoring operations making, provide innovative business models. contribute an overall competitiveness, sustainability, resilience sector as well transformation agriculture rural areas. This also provided research direction relation concept. will benefit researchers, practitioners, developers tools, policy makers supporting transition smarter more
Language: Английский
Citations
52
Artificial Intelligence in Agriculture, Journal Year: 2024, Volume and Issue: 12, P. 72 - 84
Published: April 30, 2024
The issue of food security continues to be a prominent global concern, affecting significant number individuals who experience the adverse effects hunger and malnutrition. finding solution this intricate necessitates implementation novel paradigm-shifting methodologies in agriculture sector. In recent times, domain artificial intelligence (AI) has emerged as potent tool capable instigating profound influence on sectors. AI technologies provide advantages by optimizing crop cultivation practices, enabling use predictive modelling precision techniques, aiding efficient monitoring disease identification. Additionally, potential optimize supply chain operations, storage management, transportation systems, quality assurance processes. It also tackles problem loss waste through post-harvest reduction, analytics, smart inventory management. This study highlights that how utilizing power AI, we could transform way produce, distribute, manage food, ultimately creating more secure sustainable future for all.
Language: Английский
Citations
44
Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 226, P. 109386 - 109386
Published: Sept. 6, 2024
Language: Английский
Citations
28
Artificial Intelligence in Agriculture, Journal Year: 2023, Volume and Issue: 9, P. 1 - 11
Published: June 20, 2023
In agriculture, precise fertilization and effective nutrient management are critical. Machine learning (ML) has recently been increasingly used to develop decision support tools for modern agricultural systems, including management, improve yields while reducing expenses environmental impact. ML based systems require huge amounts of data from different platforms handle non-linear tasks build predictive models that can productivity. This study reviews machine techniques estimating fertilizer status have developed in the last decade. A thorough investigation detection classification approaches was conducted, which served as basis a detailed assessment key challenges remain be addressed. The research findings suggest rapid improvements sensor technology provide cost-effective decision-making solutions. Future directions also recommended practical application this technology.
Language: Английский
Citations
38
Agronomy, Journal Year: 2023, Volume and Issue: 13(4), P. 1081 - 1081
Published: April 8, 2023
Future trends in climate change, water scarcity, and energy costs will motivate agriculturists to develop innovative agricultural systems. In order achieve sustainable farming arid regions, there is an urgent need use artificial intelligence (AI) predict estimate the optimum requirements for irrigation of date palms. Therefore, this study aimed palm depending on efficiency (WUE) yield conditions. To aim, four solar-powered micro systems were developed evaluated under six levels irrigation. Soil moisture sensor-based controllers used automate scheduling The pumping these was powered using a solar photovoltaic (PV) system. addition, machine-learning (ML) algorithms, including linear regression (LR), support vector (SVR), long short-term memory (LSTM) neural network, extreme gradient boosting (XGBoost), validated prediction purposes. These models Python programing language Keras library. results indicated that WUS achieved when maximum setpoints control adjusted at field capacity by adjusting minimum 40, 50, 70, 80% available (AW). 60, 80, 90% AW subsurface irrigation, drip bubbler respectively. dataset prepared years train test models, fifth year validate performance best model. evaluation showed LSTM followed XGBoost more accurate than SVR LR predicting requirements. validation result able all with R2 ranging from 0.90 0.92 based limited meteorological variables age. findings current demonstrated model can be powerful tool management as fast easy-to-use approach.
Language: Английский
Citations
28
Foods, Journal Year: 2023, Volume and Issue: 12(8), P. 1654 - 1654
Published: April 15, 2023
The types of artificial intelligence, intelligence integration to the food value and supply chain, other technologies embedded with adoption barriers in solutions overcome these were analyzed by authors. It was demonstrated analysis that can be integrated vertically into entire owing its wide range functions. Different phases chain are affected developed such as robotics, drones, smart machines. capabilities provided for different interaction big data mining, machine learning, Internet services, agribots, industrial robots, sensors digital platforms, driverless vehicles machinery, nanotechnology, revealed a systematic literature analysis. However, application is hindered social, technological, economic barriers. These developing financial literacy farmers disseminating good practices among participants chain.
Language: Английский
Citations
28