Deep Learning and Artificial Intelligence in Sustainability: A Review of SDGs, Renewable Energy, and Environmental Health

Sustainability, Journal Year: 2023, Volume and Issue: 15(18), P. 13493 - 13493

Published: Sept. 8, 2023

Artificial intelligence (AI) and deep learning (DL) have shown tremendous potential in driving sustainability across various sectors. This paper reviews recent advancements AI DL explores their applications achieving sustainable development goals (SDGs), renewable energy, environmental health, smart building energy management. has the to contribute 134 of 169 targets all SDGs, but rapid these technologies necessitates comprehensive regulatory oversight ensure transparency, safety, ethical standards. In sector, been effectively utilized optimizing management, fault detection, power grid stability. They also demonstrated promise enhancing waste management predictive analysis photovoltaic plants. field integration facilitated complex spatial data, improving exposure modeling disease prediction. However, challenges such as explainability transparency models, scalability high dimensionality with next-generation wireless networks, ethics privacy concerns need be addressed. Future research should focus on developing scalable algorithms for processing large datasets, exploring addressing considerations. Additionally, efficiency models is crucial use technologies. By fostering responsible innovative use, can significantly a more future.

Language: Английский

---

Artificial Intelligence and Sensor Innovations: Enhancing Livestock Welfare with a Human-Centric Approach

Human-Centric Intelligent Systems, Journal Year: 2023, Volume and Issue: 4(1), P. 77 - 92

Published: Nov. 22, 2023

Abstract In the wake of rapid advancements in artificial intelligence (AI) and sensor technologies, a new horizon possibilities has emerged across diverse sectors. Livestock farming, domain often sidelined conventional AI discussions, stands at cusp this transformative wave. This paper delves into profound potential innovations reshaping animal welfare livestock with pronounced emphasis on human-centric paradigm. Central to our discourse is symbiotic interplay between cutting-edge technology human expertise. While mechanisms offer real-time, comprehensive, objective insights welfare, it’s farmer’s intrinsic knowledge their environment that should steer these technological strides. We champion notion as an enhancer farmers’ innate capabilities, not substitute. Our manuscript sheds light on: Objective Animal Welfare Indicators: An exhaustive exploration health, behavioral, physiological metrics, underscoring AI’s prowess delivering precise, timely, evaluations. Farmer-Centric Approach: A focus pivotal role farmers adept adoption judicious utilization coupled discussions crafting intuitive, pragmatic, cost-effective solutions tailored farmers' distinct needs. Ethical Social Implications: discerning scrutiny digital metamorphosis encompassing facets like privacy, data safeguarding, responsible deployment, access disparities. Future Pathways: Advocacy for principled design, unambiguous use guidelines, fair access, all echoing fundamental principles computing analytics. essence, furnishes pioneering crossroads technology, ethics. It presents rejuvenated perspective, bridging chasm beneficiaries, resonating seamlessly ethos Human-Centric Intelligent Systems journal. comprehensive analysis thus marks significant stride burgeoning intelligent systems, especially within farming landscape, fostering harmonious coexistence animals, humans.

Language: Английский

---

Edge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(1), P. e0316920 - e0316920

Published: Jan. 16, 2025

The health of poultry flock is crucial in sustainable farming. Recent advances machine learning and speech analysis have opened up opportunities for real-time monitoring the behavior flock. However, there has been little research on using Tiny Machine Learning (Tiny ML) continuous vocalization poultry. This study addresses this gap by developing deploying ML models low-power edge devices to monitor chicken vocalizations. focus overcoming challenges such as memory limitations, processing power, battery life ensure practical implementation agricultural settings. In collaboration with avian researchers, a diverse dataset vocalizations representing range environmental conditions was created train validate algorithms. Digital Signal Processing (DSP) blocks Edge Impulse platform were used generate spectral features studying fowl vocalization. A one-dimensional Convolutional Neural Network (CNN) model employed classification. emphasizes accurately identifying categorizing different noises associated emotional states discomfort, hunger, satisfaction. To improve accuracy reduce background noise, noise-robust algorithms developed. Before removal our average F1 scores 91.6% 0.92, respectively. After removal, they improved 96.6% 0.95.

Language: Английский

---

The Impact of AI on Sustainability

Advances in systems analysis, software engineering, and high performance computing book series, Journal Year: 2024, Volume and Issue: unknown, P. 99 - 113

Published: May 15, 2024

Artificial intelligence (AI) has been increasingly popular in various businesses recent years. AI ‎proven to be an effective tool for enhancing efficiency and decision-making across industries, from ‎healthcare finance. However, sustainability is the area which having a huge impact ‎sustainability. potential transform way we think about sustainability. can find ‎trends make predictions based on massive amounts of data, allowing us understand better ‎handle environmental challenges. For example, artificial analyze weather ‎patterns predict natural disasters, improved disaster preparedness response. It ‎can also utilized industries like manufacturing transportation optimize energy usage ‎eliminate waste.‎

Language: Английский

---

Computer Vision-Based cybernetics systems for promoting modern poultry Farming: A critical review

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 225, P. 109339 - 109339

Published: Aug. 17, 2024

Language: Английский

---

Research on machine vision online monitoring system for egg production and quality in cage environment

Poultry Science, Journal Year: 2024, Volume and Issue: 104(1), P. 104552 - 104552

Published: Nov. 22, 2024

Language: Английский

---

Analyzing and forecasting poultry meat production and export volumes in Thailand: a time series approach

Cogent Food & Agriculture, Journal Year: 2024, Volume and Issue: 10(1)

Published: July 16, 2024

Amidst global food security challenges driven by population growth and economic fluctuations, the accurate prediction of production has become increasingly important. Given Thailand's position among world's top 10 poultry meat producers exporters, forecasting these figures is essential for effective planning. This study aims to analyze trends seasonal patterns forecast export volumes using various time series models. The data, which included in Thailand its volume from 2017 2023, was analyzed models including SARIMA, NNAR, ETS, TBATS, STL THETA. Forecast were constructed this study, their predictive performances evaluated compared across different results reveal consistent upward volumes. These are complemented patterns, with peaking March exhibiting a similar trajectory. High periods observed annually between September November. In terms accuracy, SARIMA model outperformed other volume, while THETA excels predicting volume. applied volumes, highlighting practical application significance context, thereby providing information planning relevant authorities stakeholders.

Language: Английский

---

Digital Phenotyping: A Game Changer for the Broiler Industry

Animals, Journal Year: 2023, Volume and Issue: 13(16), P. 2585 - 2585

Published: Aug. 10, 2023

In response to escalating global demand for poultry, the industry grapples with an array of intricate challenges, from enhancing productivity improving animal welfare and attenuating environmental impacts. This comprehensive review explores transformative potential digital phenotyping, emergent technological innovation at cusp dramatically reshaping broiler production. The central aim this study is critically examine phenotyping as a pivotal solution these multidimensional conundrums. Our investigation spotlights profound implications ‘digital twins’ in burgeoning field genomics, where production exact counterparts physical entities accelerates genomics research its practical applications. Further, probes into ongoing advancements development context-sensitive, multimodal platform, custom-built monitor health. paper evaluates platform’s revolutionizing health monitoring, fortifying resilience production, fostering harmonious balance between sustainability. Subsequently, provides rigorous assessment unique challenges that may surface during integration within industry. These span technical economic impediments ethical deliberations, thus offering perspective. concludes by highlighting game-changing identifying future directions field, underlining significance continued unlocking phenotyping’s full potential. doing so, it charts course towards more robust, sustainable, productive insights garnered hold substantial value broad spectrum stakeholders industry, setting stage imminent evolution poultry

Language: Английский

---

Poultry disease early detection methods using deep learning technology

Indonesian Journal of Electrical Engineering and Computer Science, Journal Year: 2023, Volume and Issue: 32(3), P. 1712 - 1712

Published: Nov. 8, 2023

<span>Poultry production is a pivotal contributor to global economic growth, playing central role in promoting human ecosystem sustainability. It offers affordable and readily accessible protein sources, encompassing meat, eggs, other by-products. Beyond its direct nutritional benefits, poultry enhances household income, bolsters food security, aids poverty reduction, making it integral worldwide advancement. However, as the population surges, so does demand for meat eggs. Concurrently, disease management emerges paramount challenge, leading significant threats security stability. Leveraging cutting-edge technology promising avenues devise strategies that not only bolster farm profitability but also mitigate environmental impacts foster well-being of both animals humans. This study systematically reviews latest literature concerning diagnosis based on deep learning techniques, elucidating clinical manifestations associated with various ailments. The analysis indicates emerging technological solutions, especially image processing (DL), substantially outperform conventional manual inspection methods early detection warning sector. Such innovations underscore their potential revolutionizing health mitigation.</span>

Language: Английский

---

Automatic monitoring of activity intensity in a chicken flock using a computer vision-based background image subtraction technique: an experimental infection study with fowl adenovirus

Smart Agricultural Technology, Journal Year: 2025, Volume and Issue: unknown, P. 100821 - 100821

Published: Feb. 1, 2025

Language: Английский

---