Agriculture and Human Values, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 9, 2025
Language: Английский
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
60
Horticulturae, Journal Year: 2024, Volume and Issue: 10(1), P. 49 - 49
Published: Jan. 4, 2024
This review article conducts an in-depth analysis of the role next-generation technologies in soilless vegetable production, highlighting their groundbreaking potential to revolutionize yield, efficiency, and sustainability. These technologies, such as AI-driven monitoring systems precision farming methods, offer unparalleled accuracy critical variables nutrient concentrations pH levels. However, paper also addresses multifaceted challenges that hinder widespread adoption these technologies. The high initial investment costs pose a significant barrier, particularly for small- medium-scale farmers, thereby risking creation technological divide industry. Additionally, technical complexity demands specialized expertise, potentially exacerbating knowledge gaps among farmers. Other considerations are scrutinized, including data privacy concerns job displacement due automation. Regulatory challenges, international trade regulations policy frameworks, discussed, they may need revision accommodate new concludes by emphasizing while sustainable transformative benefits, broad is constrained complex interplay financial, technical, regulatory, social factors.
Language: Английский
Citations
18
Open Access Research Journal of Engineering and Technology, Journal Year: 2024, Volume and Issue: 6(2), P. 023 - 032
Published: April 7, 2024
This study systematically reviews the transformative role of Artificial Intelligence (AI) in enhancing agricultural productivity and sustainability United States. With aim understanding how AI technologies can be effectively integrated into farming practices, this research employs a systematic literature review methodology, focusing on peer-reviewed journal articles, conference proceedings, reputable reports from 2010 to 2024. The methodology includes structured search strategy, defined inclusion exclusion criteria, thematic analysis categorize findings relevant themes. Key reveal that technologies, such as machine learning models, predictive analytics, robotics, are revolutionizing U.S. agriculture by optimizing resource use, improving crop health monitoring, decision-making processes. Despite promising potential address challenges like food security environmental sustainability, adoption faces barriers including technological adoption, data privacy concerns, need for significant investment digital infrastructure. concludes leveraging sustainable requires collaborative efforts among stakeholders, literacy, development regulatory frameworks, fostering public-private partnerships. Future directions emphasize socio-economic impacts ethical considerations, scalable solutions. underscores AI's pivotal ensuring sustainable, productive, resilient sector.
Language: Английский
Citations
18
Futurity Education, Journal Year: 2024, Volume and Issue: unknown, P. 126 - 146
Published: Feb. 13, 2024
Artificial intelligence has become a booming technology whereas it brings numerous positive changes within the educational process. The aim of research is to describe role artificial in education through analysis its opportunities and challenges. study involved integration qualitative (interviews, focus groups, classroom observations) quantitative methods (survey statistical analysis). All procedures were organized according ethical standards for data collection analysis. Over 50 recent scientific works selected analyze problem from different perspectives present comprehensive overview. 56 participants representing instructors institutions higher Ukraine. inclusion criteria based on subject specialization, institution type, curriculum accreditation, experience with technologies. It was found that impacts include personalized adaptive learning, automated administrative tasks, enhanced support, e-learning facilitation, inclusivity, data-driven decision making, gamification, increased engagement, behaviour predictive analytics, improved assessment. challenges concerned privacy, security, bias, lack understanding, transparency, necessity additional training. findings showed implementation intelligent tutoring systems, content creation Virtual Reality, chatbots can shape process effectively future modernize specialists’ results be used increase awareness using tools.
Language: Английский
Citations
14
Agricultural Systems, Journal Year: 2024, Volume and Issue: 216, P. 103908 - 103908
Published: March 2, 2024
The emergence of precision agriculture technologies has brought forward new opportunities and challenges in the agricultural sector. We delve into role living labs as dynamic platforms for fostering responsible innovation agriculture. highlight our early experiences regarding processes best practices by which an interdisciplinary research team uses a methodological approach to design test trustworthy PA innovation. Our methodology is composed five interrelated activities: (a) face-to-face interviews surveys with farmers, (b) multidimensional field data collection analysis, (c) quasi-field experiment serious games effectiveness sensor-driven performance-based payment improving ecosystem services, (d) workshops, (e) extension outreach tools knowledge farmers rural communities. initial findings demonstrate how can be leveraged co-create sustainable solutions that are socially economically responsive communities, environmentally sustainable. underscores importance including experts from various fields collaborate contribute development. share associated implementing context technologies. By sharing establishing United States, we aim promotion inclusive within lab community offer valuable guidance other researchers embarking on similar initiatives.
Language: Английский
Citations
14
Smart Agricultural Technology, Journal Year: 2024, Volume and Issue: 8, P. 100517 - 100517
Published: July 29, 2024
As per the FAO, insect pest causes 30 to 40 percent loss every year across globe. The identification, classification and management of is very important avoid significant loss. Practicing above process by adopting manual methods are time consuming less effective achieve task. traditional often fall short in addressing dynamic behaviours, resulting crop losses increased chemical usage. Therefore, adoption Artificial Intelligence (AI) techniques identification act as a good substitute that arises from challenges posed evolving populations desire for sustainable agricultural practices. AI offers transformative approach utilizing advanced algorithms analyse intricate data patterns numerous sources like sensors imagery. This enables accurate early detection, predictive modelling, enhancing decision-making control, minimizing indiscriminate pesticide application optimizing interventions. not only reduces economic but also promotes eco-friendly strategies efficient resilient systems. present review an endeavour explain intermingling future scope management.
Language: Английский
Citations
11
Cogent Food & Agriculture, Journal Year: 2025, Volume and Issue: 11(1)
Published: Jan. 20, 2025
Global food security is seriously threatened by climate change, which calls for creative agricultural solutions. However, little known about how different smart technologies are integrated to enhance security. As a strategic reaction these difficulties, this review investigates the incorporation of remote sensing (RS) as well artificial intelligence (AI) into climate-smart agriculture (CSA). This demonstrates advances can improve resilience, productivity, and sustainability utilizing AI's capacity predictive analytics, crop modelling, precision agriculture, along with RS's strengths in projections, land management, continuous surveillance. Several important tactics were covered, such combining AI RS regulate risks, maximize resource utilization, practice choices. The also discusses issues like policy frameworks, building, accessibility that prevent from being widely adopted. highlights further CSA offers insights they help ensure systems remain secure changing climates.
Language: Английский
Citations
1
IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 187 - 212
Published: Feb. 7, 2025
In a world where sustainability has been given utmost priority, agriculture plays pivotal role. Artificial Intelligence in the agricultural sector changed landscape of across globe. ‘Agvolution' (evolution agriculture) including AI supported precision farming methods, data analytics, and robotics is novel strategy which increases crop yields using less fertilizers, energy. supports ethical farming, boost revenue, lessen negative environmental effects. systems aggregate from weather stations, sensors, satellites to produce improved forecasts. This mechanism enhances sustainability. Despite numerous advantages with AI, community face challenges like security privacy, high cost machines tools. light above, authors explore usage attain sustainability, analyze need establish governance structures for increasing food overcome faced by farmers.
Language: Английский
Citations
1
Agronomy, Journal Year: 2024, Volume and Issue: 14(2), P. 239 - 239
Published: Jan. 23, 2024
Agriculture is the backbone of many economies across globe [...]
Language: Английский
Citations
7
Sustainability, Journal Year: 2024, Volume and Issue: 16(13), P. 5688 - 5688
Published: July 3, 2024
In agriculture, especially in crop breeding, innovative approaches are required to address the urgent issues posed by climate change and global food security. Artificial intelligence (AI) is a revolutionary technology wheat breeding that provides new improve ability of crops withstand produce higher yields response changing circumstances. This review paper examines incorporation artificial into conventional methods, with focus on contribution AI tackling intricacies contemporary agriculture. aims assess influence technologies enhancing efficiency, precision, sustainability projects. We conduct thorough analysis recent research evaluate several applications intelligence, such as machine learning (ML), deep (DL), genomic selection (GS). These expedite swift interpretation extensive datasets, augmenting process selecting varieties well-suited wide range environmental The findings from examined demonstrate notable progress result intelligence. ML algorithms have enhanced precision predicting phenotypic traits, whereas has reduced duration cycles. Utilizing high-throughput phenotyping allows for meticulous examination plant characteristics under different stress environments, facilitating identification robust varieties. Furthermore, AI-driven models exhibited superior predicted accuracies productivity disease resistance comparison methods. play crucial role modernization providing significant enhancements performance adaptability. integration not only facilitates growth cultivars provide large can stressful conditions but also strengthens security context change. Ongoing study collaboration across fields improving optimizing these applications, ultimately their sustainable
Language: Английский
Citations
7