Traffic congestion is a persistent problem in metropolises, leading to delays, excessive fuel consumption, and environmental pollution. Conventional traffic monitoring systems employ embedded sensors and manual superv...
详细信息
ISBN:
(数字)9798331535193
ISBN:
(纸本)9798331535209
Traffic congestion is a persistent problem in metropolises, leading to delays, excessive fuel consumption, and environmental pollution. Conventional traffic monitoring systems employ embedded sensors and manual supervision that do not provide real-time and scalable solutions. This paper offers a deep learning-based congestion prediction system employing YOLO transfer learning to detect vehicles, analyze traffic density, and classify congestion levels dynamically. The model is trained on real-world datasets, making it robust under varying lighting, weather, and traffic conditions. Unlike conventional approaches, this system monitors real-time traffic, allowing authorities to make data-driven judgments. An adaptive traffic signal management method is implemented to optimize signal durations based on congestion severity, enhancing traffic flow efficiency and minimizing wait times at crossings. By merging computer vision and artificial intelligence, this technique optimizes urban traffic management, contributes to smart city projects, and lays the groundwork for future developments in intelligent transportation systems. Future developments include refining the model for edge computing, including predictive traffic analytics, and scaling the system for large-scale implementation in urban cities.
An important objective being pursued by the European Commission is the establishment of a unified data market where stakeholders can safely and confidently share and exchange data in standardized formats. This trend i...
详细信息
smart learning analytics aims to support researchers investigating mental health by improving the interpretation of the datasets acquired from physiological biomarkers. The key enabler for emotional stress classificat...
详细信息
Convergence technologies including the Internet of Things, Big data, and Artificial Intelligence can detect and respond to dangerous situations through real-time monitoring. Meanwhile, the cafeteria environment has re...
详细信息
Water quality monitoring is a crucial aspect of public health, particularly in mitigating the risks associated with waterborne diseases and ensuring safe drinking water. Traditional monitoring methods are often labor-...
详细信息
smart city is the development direction of future urban construction and the main driving force to promote sustainable urban development. In this paper, starting from the concept of intelligent city, profound interpre...
详细信息
Effective water management is a critical component of sustainable agriculture, particularly in light of escalating water scarcity and climate challenges. This paper presents a modern solution integrating precision irr...
详细信息
ISBN:
(数字)9798331529635
ISBN:
(纸本)9798331529642
Effective water management is a critical component of sustainable agriculture, particularly in light of escalating water scarcity and climate challenges. This paper presents a modern solution integrating precision irrigation, soil moisture sensors, and real-time dataanalytics to optimize agricultural water usage. The system ensures significant water savings by delivering water directly to the root zones of crops through drip irrigation, thereby minimizing evaporation and runoff. Real-time soil moisture monitoring facilitates dynamic water distribution, achieving up to 92% irrigation efficiency and reducing water consumption by 50%. Additionally, the system demonstrates a 30% improvement in crop yields, affirming its capability to support sustainable farming practices. By leveraging IoT technologies, machine learning algorithms, and water conservation techniques, this framework offers a robust approach to addressing water management challenges. Field testing confirms that the system is a viable, efficient, and environmentally friendly alternative to traditional irrigation methods, promoting a balance between resource conservation and agricultural productivity.
This paper discusses the challenges and opportunities of the existing technologies and practices in the context of smart City and Future Mobility to cope with pandemics. The overview shows a need to accelerate the dep...
详细信息
Precision agriculture struggles with scalability, data integration, and decision-making, prompting innovative solutions. Recent advancements like CNNs and cloud computing provide interesting answers but confront chall...
详细信息
ISBN:
(数字)9798350379990
ISBN:
(纸本)9798350391558
Precision agriculture struggles with scalability, data integration, and decision-making, prompting innovative solutions. Recent advancements like CNNs and cloud computing provide interesting answers but confront challenges. data quality, processing needs, interoperability, and real-time decision-making are issues. These difficulties demand innovative data synchronization, model dependability, and system scalability methods. This project uses sophisticated analytics and cloud technology to improve nutrient management systems. Improving scalability, accuracy, and efficiency while presenting unique data fusion and user-friendly interfaces are goals. Clear problems and goals guide the study's scope and purpose. Wireless soil nutrient sensors can capture real-time data on important soil factors such as pH levels, the amount of nitrogen, phosphate, and potassium present, and more. This information is then sent to a platform hosted in the cloud, where it is processed using sophisticated dataanalytics and machine learning algorithms, in addition to previous crop performance data and agronomic models. The program will create tailored suggestions for nutrient management, including topics such as the kinds of fertilizer, application rates, and the best time. These proposals give farmers more agency, allowing them to make educated decisions via an easily navigable interface. Because of the system's ability to react to changing circumstances and its continual monitoring, nutrient management techniques are kept in sync with those changes throughout the crop's life cycle.
As a standardized and systematic management method, business process management plays an important role in the industrial Internet of Things (IIoT) scenario. With the rapid development of mobile Internet and the incre...
详细信息
暂无评论