In urban environments, efficient ambulance response times are critical for saving lives. This paper proposes a novel approach utilizing a multi-sensor integration system for improving ambulance control and traffic man...
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ISBN:
(纸本)9798350364828
In urban environments, efficient ambulance response times are critical for saving lives. This paper proposes a novel approach utilizing a multi-sensor integration system for improving ambulance control and traffic management. The system combines Radio Frequency Identification (RFID) sensors, cameras, and microphones to enhance the responsiveness of ambulance drivers and alleviate traffic congestion. The RFID sensors are strategically placed along the ambulance route to facilitate seamless communication between the ambulance and traffic signals. When an ambulance approaches, the RFID sensors trigger pre-programmed traffic signal adjustments, such as extending green lights or halting conflicting traffic flow, to expedite the ambulance's passage. Simultaneously, the camera-based detection system identifies the presence of ambulances in traffic and assesses congestion levels in real-time. Utilizing computer vision algorithms, the system analyzes live camera feeds to detect ambulance vehicles and evaluate traffic density and movement patterns. This information enables dynamic rerouting of ambulances to less congested routes, optimizing response times and minimizing delays. Furthermore, a microphone array is employed to detect the distinct audio signature of ambulance sirens. By leveraging sound analysis techniques, the system accurately identifies the approach of an ambulance and triggers additional traffic management measures, such as prioritizing ambulance lanes or temporarily rerouting vehicles to clear a path. Integration of these sensor technologies into a unified control system offers a comprehensive solution for improving ambulance navigation through urban traffic. Through proactive traffic signal adjustments, dynamic route optimization, and real-time siren detection, the proposed system enhances overall emergency response effectiveness while reducing the risk of traffic-related delays and accidents. Moreover, the system's adaptability and scalability make it suit
The quality of human life is improving over a period of time with the technological advancements in the arena of Artificial Intelligence and Internet of Things. Various fields adopt and implement automation process fo...
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Object recognition algorithms need to be very accurate and efficient in order for autonomous navigation systems to see and securely interact with their surroundings. Although conventional computer vision techniques ha...
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The innovative design of remote intelligentcontrol system for mining dampers is of great significance for enhancing the safety and efficiency of mine operations. This paper adopts the TRIZ innovation method to conduc...
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Road commuting often bears unnoticed risks, contributing significantly to fatalities and injuries across the world. Alarmingly, India tops the list of harm caused by road accidents with 1.5 million annual road fatalit...
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The parameters of quality control and quality inspection are considered as important factors affecting market demand, and the "ERC" fairness preference model is introduced to construct a supply chain quality...
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ISBN:
(纸本)9781643683850
The parameters of quality control and quality inspection are considered as important factors affecting market demand, and the "ERC" fairness preference model is introduced to construct a supply chain quality control decision model when the retailer and the manufacturer have fair preferences respectively. Through numerical calculation examples, we further observe the internal relationship between quality control variables and other parameters such as product price and market demand in case of the retailer and the manufacturer with fairness preferences respectively, and suggest to improve product quality by establish cooperative mechanism through supply chain parties. This is an important guide to the overall optimization of the supply chain.
With the progress of science and technology nowadays and the enhancements in control system optimization field, system fault diagnosis has become a hot topic in the industry, and many models of fault diagnosis using v...
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With the progress of science and technology nowadays and the enhancements in control system optimization field, system fault diagnosis has become a hot topic in the industry, and many models of fault diagnosis using various artificial intelligence algorithms have emerged. However, with the increasing complexity of fault, the accuracy of fault diagnosis from a single data source gradually declines. Based on this, this paper proposal an intelligent diagnosis model innovationally basing on multi-sensor intelligent fusion algorithm, which uses BP neural network, a typical artificial intelligence algorithm, to generate evidence from multi-sensor data, on this basis, D-S evidence theory is used for data fusion to improve the accuracy of fault diagnosis and the performance of fault diagnosis algorithm in multi-type control systems.
At present, PDC bits are still brazed by artificial flame, and the welding quality is not stable enough. In order to solve this problem, a new type of intelligent temperature control device is developed by combining t...
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Aims to develop web application for information management and sharing which helps educational institutions broadcast information to the students and their faculties. A college generates and uses a large amount of dat...
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With the rapid development of technology, autonomous driving technology has gradually become a research hotspot in the automotive industry. This article proposes a new design scheme for an intelligent vehicle autonomo...
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