CLOUD AI SYSTEM FOR REAL-TIME PEDESTRIAN AND TRAFFIC SAFETY MANAGEMENT IN SMART CITIES USING 5G AND DISTRIBUTED EDGE DEVICES

Abstract

A cloud ai system for real-time pedestrian and traffic safety management in smart cities using 5g and distributed edge devices comprises RTPTSTMD Mote boasts processing modules, precise sensors, and a solar supply, facilitating the continuous recording and analysis of traffic times for the efficient management and monitoring to generate timely warnings to protect the security of the city thanks to the RTPTSRGMD Mote's capabilities, the remote processors, sensor board, and the touch screen allow for real-time traffic surveys and prediction of on-site decisions without needing to move around.

Specification

Description:FIELD OF THE INVENTION
This invention relates to cloud ai system for real-time pedestrian and traffic safety management in smart cities using 5g and distributed edge devices.
BACKGROUND OF THE INVENTION
This invention proposes an AI based solution which is integrated with cloud computing for deployment in smart cities equipped with various distributed edge devices and networks for management of pedestrian and traffic safety in real time. Such a solution comprises of a smart traffic device which monitors and analyses pedestrian and vehicle activity in real time as well as a portable smart device that informs driver traffic management through AI powered analytics, and recommends control measures. Information gathered from such environment and traffic sensors is processed at the site and sent to a dedicated cloud server so that machine learning based analysis and monitoring can be performed for predictive recommendations. The system allows operators to get near real time data through visualisation of the dashboard view on the web and on a mobile device for informed decisions to be made by relevant operators and persons in authority. The present solution is also sustainable, scalable and addresses important problems of urban pedestrian & traffic management as well as safety through intelligent and effective use of data.
This invention solves the important problems of crime and traffic accident prevention and traffic management in the context of continuous urban population growth and the expansion of vehicular traffic and pedestrians activities, which often results in space and time accidents, factors and other inefficiencies. Conventional traffic management systems are characterized by weak feedback mechanisms owing to the lack of integrated real-time situation monitoring capability, predictive analytics, and automated recommendations; this results in inefficient decision making and response times. The problems are compounded by the limitations posed by lack of comprehensive systems to observe environmental conditions, or measure traffic and pedestrian activity. This innovation fills this gap through the use of AI-based concepts and solutions that enable the acquisition and communication of appropriate information for effective analysis to be done which is critical in decision making. This ultimately leads to improved safety on the roads, fewer accidents as well as better traffic management in ways that are economically viable and environmentally sustainable.
CN112837535B: The disclosure provides a traffic information processing method, a device, a system, equipment and a storage medium, and relates to the fields of vehicle-road coordination, intelligent high-speed, intelligent road network, deep learning and the like. The method comprises the following steps: acquiring information of a target road section, wherein the information of the target road section comprises: at least one of environmental weather information, full element traffic element awareness information, and road infrastructure information; formulating early warning information related to traffic safety according to the information of the target road section; and sending the early warning information related to the traffic safety to a designated receiving module related to the target road section. According to the embodiment of the disclosure, 100% of driver early warning can be realized, meanwhile, active perception of all-element traffic elements under the influence of all traffic factors such as weather, road infrastructure, traffic incidents and the like can be realized, active early warning can be realized, management and control can be performed, and all-weather road traffic safety trip is ensured.
RESEARCH GAP: The integration of 5G-enabled distributed edge devices with AI-driven real-time pedestrian and traffic safety analytics for smart cities is the novelty of the system.
US10991243B2: Embodiments describe new mechanisms for signalized intersection control. Embodiments expand inputs beyond traditional traffic control methods to include awareness of agency policies for signalized control, industry standardized calculations for traffic control parameters, geometric awareness of the roadway and/or intersection, and/or input of vehicle trajectory data relative to this intersection geometry. In certain embodiments, these new inputs facilitate a real-time, future-state trajectory modeling of the phase timing and sequencing options for signalized intersection control. Phase selection and timing can be improved or otherwise optimized based upon modeling the signal's future state impact on arriving vehicle trajectories. This improvement or optimization can be performed to reduce or minimize the cost basis of a user definable objective function.
RESEARCH GAP: The integration of 5G-enabled distributed edge devices with AI-driven real-time pedestrian and traffic safety analytics for smart cities is the novelty of the system.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
This innovation functions as a complex framework which adds value in enhancing pedestrian and traffic safety by monitoring, analyzing, and making decisions in real time. It particulary comprises two devices which are related to each other, the fixed traffic governance device, and the mobile monitoring and guidance device. These devices retrieve information, process it through neural networks, and provide useful insights to the operators in the field and other relevant stakeholders. The fixed traffic governance device is placed at strategic places to oversee traffic and the movement of pedestrians in real-time. Through a variety of sensors and analytical skills, the device collects movement of vehicles, movement of people, environmental conditions and even the potential risk factors to safety. Such information is acted on immediately to reduce the time lag in identifying traffic or safety problems. At the same time, information already processed is sent through the cloud to further analysis using high speed communication techniques. In the cloud, models derived from machine learning are more advancing in that they detect whether there were any patterns, risks present, and even recommend how best traffic can be managed and control.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a"," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", "third", and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
This innovation functions as a complex framework which adds value in enhancing pedestrian and traffic safety by monitoring, analyzing, and making decisions in real time. It particulary comprises two devices which are related to each other, the fixed traffic governance device, and the mobile monitoring and guidance device. These devices retrieve information, process it through neural networks, and provide useful insights to the operators in the field and other relevant stakeholders. The fixed traffic governance device is placed at strategic places to oversee traffic and the movement of pedestrians in real-time. Through a variety of sensors and analytical skills, the device collects movement of vehicles, movement of people, environmental conditions and even the potential risk factors to safety. Such information is acted on immediately to reduce the time lag in identifying traffic or safety problems. At the same time, information already processed is sent through the cloud to further analysis using high speed communication techniques. In the cloud, models derived from machine learning are more advancing in that they detect whether there were any patterns, risks present, and even recommend how best traffic can be managed and control.
By utilizing real-time data and analytics, the portable monitoring and guidance device allows operators and field staff to hold a handheld tool. All safety advice, forecast notifications and environmental information are shown on an easily operated interface. The device guarantees that operators can act on sudden events even if they are not in the control room. The joined work of the portable device, the stationary system and the cloud server allows sending and receiving the information constantly. In short, the system fuses the distributed intelligence at the local edge of the network with the corresponding intelligence available in the cloud for efficient and effective traffic management. This innovation integrates real-time monitoring, predictive analytics, and actionable guidance to improve the safety of urban areas, prevent accidents, and enhance the performance of traffic systems in smart cities.
BEST METHOD OF WORKING
The RTPTSTMD Mote boasts processing modules, precise sensors, and a solar supply, facilitating the continuous recording and analysis of traffic times for the efficient management and monitoring to generate timely warnings to protect the security of the city.
Thanks to the RTPTSRGMD Mote's capabilities, the remote processors, sensor board, and the touch screen allow for real-time traffic surveys and prediction of on-site decisions without needing to move around.
The integrated 5G Communication Module boosts the exchange of information with a custom cloud server, which is embedded in both the RTPTSTMD Mote and the RTPTSRGMD Mote, to enable the integration of and provision for the seamless incorporation of edge analytics and cloud monitoring in the traffic control system.
The Capacitive Touch Screen Display enables field workers to interpret data in real time and view what has been suggested to assist in the respective situation. Such an aspect enhances the understanding of the environment and allows for greater safety to be adhered to.
The LiDAR and Ultrasonic Sensors integrated in the RTPTSTMD Mote assist in accurately detecting obstacles and the density of traffic, thereby improving the system's functionality in regard to the stability of movement in the urban area.
ADVANTAGES OF THE INVENTION
1. A notable edge is provided by the Jetson Nano and Intel NUC that enables edge computing for the processing of information on the spot in order for there to be instant detection of traffic incident, a person's activity and sources of threats.
2. Integration of 5G GPRS Modem enhances the communication speed between an edge device and the cloud servers and ensures that data is transferred and analysis and suggestions are provided instantly.
3. LiDAR sensors, ultrasonic sensors and a camera module make it possible to keep track of cars and pedestrians movements with a high level of accuracy, which leads to the development of situational awareness and risk management.
4. The stationary unit has a Solar Powered Power Supply Unit that designs the unit operationally efficient while the handheld device has a rechargeable battery which boosts its portability and usability in different environment contexts.
5. The capacitive touch screen display in the handheld can allow operators to have easy and real time viewing of the data as well as the alerts and suggestions that can be taken as immediate action.
6. With the computing capabilities offered by the Jetson Nano and the cloud, the system is known to harness the capabilities of AI and machine learning for predictive analytics and actionable intelligence thereby minimizing accidents and enhancing the management of traffic.
, Claims:1. A cloud ai system for real-time pedestrian and traffic safety management in smart cities using 5g and distributed edge devices comprises RTPTSTMD Mote boasts processing modules, precise sensors, and a solar supply, facilitating the continuous recording and analysis of traffic times for the efficient management and monitoring to generate timely warnings to protect the security of the city.
2. The system as claimed in claim 1, wherein thanks to the RTPTSRGMD Mote's capabilities, the remote processors, sensor board, and the touch screen allow for real-time traffic surveys and prediction of on-site decisions without needing to move around.
3. The system as claimed in claim 1, wherein the integrated 5G Communication Module boosts the exchange of information with a custom cloud server, which is embedded in both the RTPTSTMD Mote and the RTPTSRGMD Mote, to enable the integration of and provision for the seamless incorporation of edge analytics and cloud monitoring in the traffic control system.
4. The system as claimed in claim 1, wherein the Capacitive Touch Screen Display enables field workers to interpret data in real time and view what has been suggested to assist in the respective situation, such an aspect enhances the understanding of the environment and allows for greater safety to be adhered to.
5. The system as claimed in claim 1, wherein the LiDAR and Ultrasonic Sensors integrated in the RTPTSTMD Mote assist in accurately detecting obstacles and the density of traffic, thereby improving the system's functionality in regard to the stability of movement in the urban area.

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