Integrating Artificial Intelligence Agents with the Internet of Things for Enhanced Environmental Monitoring: Applications in Water Quality and Climate Data

Electronics, Journal Year: 2025, Volume and Issue: 14(4), P. 696 - 696

Published: Feb. 11, 2025

The integration of artificial intelligence (AI) agents with the Internet Things (IoT) has marked a transformative shift in environmental monitoring and management, enabling advanced data gathering, in-depth analysis, more effective decision making. This comprehensive literature review explores AI IoT technologies within sciences, particular focus on applications related to water quality climate data. methodology involves systematic search selection relevant studies, followed by thematic, meta-, comparative analyses synthesize current research trends, benefits, challenges, gaps. highlights how enhances IoT’s collection capabilities through predictive modeling, real-time analytics, automated making, thereby improving accuracy, timeliness, efficiency systems. Key benefits identified include enhanced precision, cost efficiency, scalability, facilitation proactive management. Nevertheless, this encounters substantial obstacles, including issues quality, interoperability, security, technical constraints, ethical concerns. Future developments point toward enhancements technologies, incorporation innovations like blockchain edge computing, potential formation global systems, greater public involvement citizen science initiatives. Overcoming these challenges embracing new technological trends could enable play pivotal role strengthening sustainability resilience.

Language: Английский

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Advanced sensors, monitoring, and control systems for environmental sustainability

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 47 - 55

Published: Jan. 1, 2025

Language: Английский

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Harnessing Artificial Intelligence, Machine Learning and Deep Learning for Sustainable Forestry Management and Conservation: Transformative Potential and Future Perspectives

Plants, Journal Year: 2025, Volume and Issue: 14(7), P. 998 - 998

Published: March 22, 2025

Plants serve as the basis for ecosystems and provide a wide range of essential ecological, environmental, economic benefits. However, forest plants other systems are constantly threatened by degradation extinction, mainly due to misuse exhaustion. Therefore, sustainable management (SFM) is paramount, especially in wake global climate change challenges. SFM ensures continued provision forests both present future generations. In practice, faces challenges balancing use conservation forests. This review discusses transformative potential artificial intelligence (AI), machine learning, deep learning (DL) technologies management. It summarizes current research technological improvements implemented using AI, discussing their applications, such predictive analytics modeling techniques that enable accurate forecasting dynamics carbon sequestration, species distribution, ecosystem conditions. Additionally, it explores how AI-powered decision support facilitate adaptive strategies integrating real-time data form images or videos. The manuscript also highlights limitations incurred ML, DL combating management, providing acceptable solutions these problems. concludes perspectives immense modernizing SFM. Nonetheless, great deal has already shed much light on this topic, bridges knowledge gap.

Language: Английский

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Integrating artificial intelligence in biodiversity conservation: bridging classical and modern approaches

Biodiversity and Conservation, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Language: Английский

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A Systematic Review of the Application of Remote Sensing Technologies in Mapping Forest Insect Pests and Diseases at a Tree-Level.

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: 36, P. 101341 - 101341

Published: Sept. 4, 2024

Language: Английский

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Blockchain Technology for Wildlife Conservation

Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 183 - 212

Published: Jan. 10, 2025

Blockchain Technology has shown a tremendous increase in application various fields. based having its roots from Cryptocurrency and spread branches healthcare, Financial Services, Supply chain management, many more industries. Blockchain's innovative solutions are necessary to protect wildlife ecosystems growing threats such as poaching, habitat destruction, climate change, which threaten global biodiversity. technology integrated with IoT shows potential for uses conservation. This chapter aims amalgamate blockchain Wildlife conservation, will address serious challenges maintaining data integrity security, tampering of data, smart contracts, tokenization. The decentralized ledger the Internet Things offers strong foundation monitoring origin flow products, fighting against illegal trade through transparency adherence regulations. provides unchangeable records conservation being altered, giving researchers policymakers trustworthy information making decisions. Furthermore, improve distribution supervision funds by utilizing contracts automate processes transparency. How this cutting-edge can current contribute preservation biodiversity is examined intersection explored chapter. Moreover, could enhance cohesion local communities providing incentives, token-based rewards, encourage participation efforts. dedication encourages eco-friendly practices strengthens collective effort wildlife. examine case studies where been successfully implemented highlighting opportunities associated adoption. Finally, we analyse applications future potential, also provide insights into how revolutionize

Language: Английский

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Forestry Segmentation Using Depth Information: A Method for Cost Saving, Preservation, and Accuracy

Forests, Journal Year: 2025, Volume and Issue: 16(3), P. 431 - 431

Published: Feb. 27, 2025

Forests are critical ecosystems, supporting biodiversity, economic resources, and climate regulation. The traditional techniques applied in forestry segmentation based on RGB photos struggle challenging circumstances, such as fluctuating lighting, occlusions, densely overlapping structures, which results imprecise tree detection categorization. Despite their effectiveness, semantic models have trouble recognizing trees apart from background objects cluttered surroundings. In order to overcome these restrictions, this study advances management by integrating depth information into the YOLOv8 model using FinnForest dataset. Results show significant improvements accuracy, particularly for spruce trees, where mAP50 increased 0.778 0.848 mAP50-95 0.472 0.523. These findings demonstrate potential of depth-enhanced limitations RGB-based segmentation, complex forest environments with structures. Depth-enhanced enables precise mapping species, health, spatial arrangements, habitat analysis, wildfire risk assessment, sustainable resource management. By addressing challenges size, distance, lighting variations, approach supports accurate monitoring, improved conservation, automated decision-making forestry. This research highlights transformative integration models, laying a foundation broader applications environmental conservation. Future studies could expand dataset diversity, explore alternative technologies like LiDAR, benchmark against other architectures enhance performance adaptability further.

Language: Английский

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Digital technologies for the Sustainable Development Goals

Green Technologies and Sustainability, Journal Year: 2025, Volume and Issue: unknown, P. 100202 - 100202

Published: March 1, 2025

Language: Английский

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Green Technologies and Policies for Forest Conservation in South and Southeast Asia

Actualidad Jurídica Ambiental, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 34

Published: April 11, 2025

Abstract: Green technologies are very relevant when it comes to implementing good practices in sustainable forest management as well the conservation of forests world today. Technologies like satellite, AI, IoT, and blockchain, mean that there tools support real-time trackers, preventing illicit acts logging, better utilising resources at hand. These made possible for decision making based on values new environment allows fast response fires pests. In addition, green can also improve prospects reforestation with accuracy planting data mining. Other financial strategies include finance, carbon supply chain supporting protection, promoting private capital conservation. The efficient deployment needs sound policy environment, backing, multiple stakeholder engagements. order achieve this is a need governments, businesses, local communities cooperate developing proper legal frameworks will force people adopt technologies, while same time sure benefits have reach out areas most affected by deforestation. As such, future remains further evolution these their implementation into overall environmental economic policies. With connection technological change governance our planet, forestry, climate change, biodiversity assets may be protected preserved use generations. Resumen: Las tecnologías verdes son muy importantes la hora de aplicar buenas prácticas en gestión forestal sostenible y conservación los bosques el mundo actual. Tecnologías como satélite, IA, significan que hay herramientas para apoyar rastreadores forestales tiempo real, prevención actos ilícitos tala, una mejor utilización recursos mano.Estas hacen posible toma decisiones basada valores un nuevo entorno permite responder con rapidez incendios las plagas. Además, también pueden mejorar perspectivas reforestación plantación precisión extracción datos.Otras estrategias financieras incluyen financiación verde, del carbono cadena suministro protección promover privado conservación. El despliegue eficaz requiere político sólido, respaldo financiero participación múltiples partes interesadas. Para lograrlo, es necesario gobiernos, empresas comunidades locales cooperen desarrollo marcos jurídicos adecuados obliguen gente adoptar verdes, asegurándose al mismo beneficios tienen llegar zonas más afectadas por deforestación.Así pues, futuro sigue dependiendo evolución estas su aplicación políticas medioambientales económicas generales.Con conexión adecuada cambio tecnológico futura gobernanza nuestro planeta, activos forestales, climático biodiversidad podrán protegerse conservarse uso generaciones venideras. Keywords: technologies. Forests. Financial banking. Climate change. Forest Legal frameworks. Palabras clave: verdes. Bosques. Banca financiera. Cambio climático. Conservación bosques. Marcos jurídicos. Index: 1. Introduction 2. Current regulatory 2.1. ASEAN’S political regulations 2.2. International treaties 2.3. United Nations REDD+ Program Its Implication Forests 2.4. Challenges current 3. Use technology 3.1. Potential Technology Management Conservation 3.2. Policy Implications Robust Application 3.3. Governance: Integrating Making 4. Case studies 5. Future Directions 6. Conclusion 7. References Índice: Introducción normativos actuales Entorno normativa ASEAN Tratados internacionales Programa Naciones Unidas implicación Desafíos políticos Uso tecnología Potencial verde Implicaciones sólida Gobernanza verde: Integración elaboración Casos prácticos Orientaciones futuras Conclusión Referencias

Language: Английский

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Harnessing the Power of Artificial Intelligence in Climate Change Mitigation: Opportunities and Challenges for Public Health

Published: March 6, 2024

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze predict climatic patterns, AI offers opportunities enhance resource management develop effective strategies mitigation. Moreover, can contribute generating sustainable solutions that address complex interconnected nature of change. For example, enable optimization energy consumption facilitate integration renewable sources into existing systems. It also support development models provide timely accurate predictions, enabling policymakers implement proactive measures disaster preparedness response. Furthermore, AI-powered disease surveillance mitigation techniques improve health outcomes identifying patterns trends in spread diseases relation factors.However, widespread adoption AI-based is not without challenges. Ethical concerns surrounding privacy data ownership must be addressed, use requires access large datasets, raising potential risks. Technical constraints, such limited computational power need sophisticated algorithms, pose obstacles implementation strategies. issues related accessibility affordability technologies resolved ensure equitable distribution maximize health.To fully harness improving outcomes, it crucial promote innovation, multidisciplinary collaboration, open science. Innovation drive new algorithms specifically tailored Multidisciplinary approaches bring together experts from diverse fields, including science, health, computer foster holistic understanding systems design comprehensive solutions. Finally, science practices, sharing collaboration accelerate progress mitigating impacts.In conclusion, promising effectively However, realize potential, essential tackle ethical concerns, overcome technical affordability. promoting we unlock transformative outcomes.

Language: Английский

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