Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 335 - 379
Published: Jan. 1, 2025
Language: Английский
Published: May 3, 2025
Language: Английский
Citations
0
International Journal of Management Technology and Social Sciences, Journal Year: 2024, Volume and Issue: unknown, P. 283 - 301
Published: June 30, 2024
Background/Purpose: The agriculture sector is the backbone of every nation which contributes to global economy. implementation technology in has brought revolutionary development its outcome. Due this, a drastic improvement economy from agricultural expected. Moreover, artificial intelligence (AI) improves productivity farmers giving solutions various challenges faced by farmers. AI tools that are developed for include precision farming, predictive analytics, automated machinery, smart irrigation systems, crop and soil monitoring, supply chain optimization, weather forecasting, livestock management. Adopting faces several despite long-term benefits. high upfront costs be invested implementing make it difficult small-scale developing invest AI. Implementing above needs technical skills, fast internet connectivity, costlier equipment. lack above-mentioned requirements, technologies meant do not reach This results wastage resources without Considering issues an appropriate simplified model proposed facilitates adaptation small medium-scale their improve performance. Objective: objective this paper review journals related Agriculture study implementation. It also aims at identifying research gap will help develop suitable end like Design/Methodology/Approach: A systematic literature was conducted gathering examining relevant international national journals, conferences, databases, other accessed via Google Scholar search engines. Findings/Result: sector, crucial nation's economy, seen advancements through technology, especially promise enhance address challenges. However, costs, resistance new technologies, necessary infrastructure hinder widespread adoption among To overcome these obstacles, effectively support adopting boost Originality/Value: ML diverse sources done. area due recent agriculture. information acquired create improving outcomes existing scenario. Paper Type: Literature Review.
Language: Английский
Citations
3
Journal of Sensors, Journal Year: 2024, Volume and Issue: 2024(1)
Published: Jan. 1, 2024
Growing worldwide waste management challenges have prompted research efforts for sustainable solutions, especially in green energy technologies. This study highlights robotics’ critical role modern by putting forth a novel strategy incorporating cutting‐edge The aims to create an effective monitoring system measure the amounts of methane gas and organic at disposal sites. main component this method is 3D‐printed spider robot driven servo motor with solid flexible claws. robotic communicates level readings ThingSpeak platform on Internet Things, while it navigates sites autonomously. also investigates how develop systems more economically efficiently using portable, low‐power microcontroller, such as Arduino Nano. uses rigorous testing methodology assess performance viability microcontroller system. results are expected emphasise practical economic development approach offering insightful information developing
Language: Английский
Citations
3
AI Computer Science and Robotics Technology, Journal Year: 2024, Volume and Issue: 3
Published: Oct. 3, 2024
The integration of artificial intelligence (AI) and machine learning (ML) into crop management is transforming modern agriculture by enhancing efficiency, sustainability, resilience. This review explores the multifaceted applications AI ML in key areas such as precision farming, pest disease management, harvest optimization. use AI-driven predictive analytics allows for more accurate forecasting yields, outbreaks, weather conditions, enabling farmers to make data-driven decisions that optimize resource reduce environmental impacts. A significant advancement with Internet Things (IoT) autonomous farming equipment. These technologies enable real-time monitoring precise interventions, productivity minimizing labor costs. In breeding genomics, accelerates development resilient varieties, which crucial adapting climate change increasing food demands. Despite many benefits, challenges data quality, infrastructure limitations, high implementation costs remain. adoption uneven, small-scale developing regions facing barriers due limited access resources. Ethical concerns related privacy digital divide must also be addressed ensure equitable these technologies. future lies advanced models, enhanced IoT, widespread systems.
Language: Английский
Citations
3
Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 335 - 379
Published: Jan. 1, 2025
Language: Английский
Citations
0