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An Efficient Way to Vehicle Movement Monitor in Flooded Underpasses and Tunnels Using IoT

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An Efficient Way to Vehicle Movement Monitor in Flooded Underpasses and Tunnels Using IoT

ORDINARY APPLICATION

Published

date

Filed on 16 November 2024

Abstract

Urban infrastructure faces significant challenges due to waterlogging in underpass and tunnel during heavy rainfall. This leads to traffic gridlocks, vehicle immobilization, and even accidents. The existing systems fail to provide real-time, accurate monitoring or adequate response mechanisms. Our system proposes an IoT-based solution to monitor water levels in underpasses and tunnels, offering real-time updates to drivers and authorities. Using sensors controlled by an ESP32 board, data is continuously uploaded to the cloud. This allows vehicles to be rerouted efficiently and helps prevent accidents. An LCD screen at the underpass and tunnel displays real-time water levels, informing drivers of safe passage. Additionally, a DC motor pump is activated when water levels exceed the safe threshold, ensuring rapid water clearance. This cost-effective solution ensures public safety and reduces traffic disruptions during floods.

Patent Information

Application ID202441088791
Invention FieldCOMPUTER SCIENCE
Date of Application16/11/2024
Publication Number47/2024

Inventors

NameAddressCountryNationality
Dr. Ramya R SDepartment of Computer Science & Engineering, Dayananda Sagar College of Engineering, Bangalore-560111IndiaIndia
Dr. Deepak GDepartment of Computer Science & Engineering, Dayananda Sagar College of Engineering, Bangalore-560111IndiaIndia
D RavikumaraDepartment of Computer Science & Engineering, Dayananda Sagar College of Engineering, Bangalore-560111IndiaIndia
Lakshmi DDepartment of Computer Science & Engineering, Dayananda Sagar College of Engineering, Bangalore-560111IndiaIndia
Nuthana SDepartment of Computer Science & Engineering, Dayananda Sagar College of Engineering, Bangalore-560111IndiaIndia
Rahul RDepartment of Computer Science & Engineering, Dayananda Sagar College of Engineering, Bangalore-560111IndiaIndia

Applicants

NameAddressCountryNationality
Dayananda Sagar College of EngineeringShavige Malleshwara Hills, Kumaraswamy Layout, BangaloreIndiaIndia

Specification

Description:FIELD OF INVENTION
[001] This invention relates to the field of smart infrastructure, particularly focusing on the development of advanced IoT-based and deep-learning-driven systems for detecting and monitoring waterlogging in urban environments underpasses and tunnels.
BACKGROUND AND PRIOR ART
[002] Flooded underpasses and tunnels, especially in urban environments, have historically caused significant traffic disruptions and accidents due to waterlogging. Traditionally, there has been no real-time, automated system to monitor water levels in these areas, leaving drivers unaware of flood risks. Existing methods rely on passive data collection, such as news reports, social media, or manual checks, leading to delayed or inaccurate information dissemination.
[003] Previous solutions have attempted to integrate basic sensor systems to detect water levels, but these lacked the automated connectivity and real-time communication features essential for immediate and effective response. With advancements in the Internet of Things (IoT), modern systems now propose using water level sensors, and ESP32 board, for data transmission to the cloud. This data can then be displayed on LCD screens near the underpass and tunnel accessed through mobile apps, enabling drivers to make informed decisions. Additionally, the implementation of automated water pumps activated when water levels exceed predefined thresholds offers a proactive way to reduce water accumulation in underpasses and tunnels.
[004] The proposed system offers a low-cost, efficient solution by integrating hardware and IoT technology to monitor and manage water levels, reducing the need for manual interventions and improving traffic safety.
SUMMARY OF THE INVENTION
[005] The invention provides a comprehensive solution for monitoring waterlogging in underpasses and tunnels. The system comprises IoT sensors that collect real-time environmental data, including images of entry, exit of underpass and tunnel environment. It integrates object detection technologies to provide detailed information about vehicles classification and number plate detect, all communicated through an IoT framework for real-time updates. This enables city officials and transportation authorities to take proactive measures in managing waterlogged underpasses and tunnels, avoiding disruptions in traffic flow and ensuring safety.
[006] The system also has the potential to integrate with existing infrastructure monitoring platforms, offering a seamless and scalable solution that can be deployed across multiple underpasses and tunnels in any city.
BRIEF DESCRIPTIONS OF DRAWINGS:
[007] Figure 1: Depicts the IoT sensor network setup in an underpass and tunnel, illustrating the strategic placement of various sensors such as water level sensors, and cameras at critical points to monitor environmental conditions. These sensors communicate by establishing pathways for real-time data transmission. The data collected from the sensors is transmitted for analysis further.
[008] Figure 2: Illustrates the deep learning-based real-time object detection model architecture, which leverages Convolutional Neural Networks (CNNs) framework. This architecture is designed to detect waterlogged areas effectively. The model processes input images from IoT-connected cameras, where CNN layers extract important visual features related to water accumulation.
[009] Figure 3: Provides a detailed overview of the entire system workflow, starting with the initial data collection phase where IoT sensors are deployed to monitor various environmental parameters. The collected data is then used in deep learning models specifically designed to detect instances of waterlogging. Once the detection process is complete, the system facilitates the real-time upload of this processed data to the cloud.
[010] Figure 4: Illustrates the process of analysing real-time data uploaded to the cloud to identify and assess flooded areas. Once the data is processed, the system integrates with Google Maps to visually mark the locations of these flooded areas. This mapping functionality helps in generating alert messages that are then communicated to drivers. The alerts provide crucial information about road conditions, enhancing safety by informing drivers of potential hazards in their route.
DETAILED DESCRIPTION OF THE INVENTION
[011] The invention integrates a three-stage process to accurately detect and monitor waterlogging in underpasses and tunnels.
[012] The first stage of the invention focuses on the detection and monitoring of water levels within underpasses and tunnels using advanced IoT sensors. This stage begins with the strategic installation of these sensors throughout the underpass and tunnel. These sensors are designed to continuously measure water depth and collect real time data.
[013] As the sensors gather real-time data, it permitted and informed decisions regarding vehicle access to the underpass and tunnel. If the detected water level exceeds predefined thresholds indicating that it is too high for safe passage the system activates a series of automated responses. These responses include sending alerts and closing the gates at both ends of the underpass and tunnel to prevent vehicles from entering. This proactive measure is designed to avoid potential accidents and ensure the safety of both the vehicles and the infrastructure. The data collected during this stage is crucial for managing subsequent actions, including the activation of drainage systems and pumps in later stages.
[014] The system focuses on real-time vehicle detection, classification, and monitoring within an underpass and tunnel. Fixed cameras, positioned at both the entry and exit points, capture high-resolution images of each vehicle. Deep learning models analyse this data to classify vehicles into categories such as buses, trucks, and small vehicles is employed to read and record their number plates. The system continuously monitors the time each vehicle takes to traverse the underpass and tunnel. If a vehicle does not exit within a predefined period, the system flags this delay as an anomaly, potentially indicating issues like a breakdown or waterlogging. An automated alert, containing the vehicle's number plate and classification details, is generated and forwarded to the rescue team or emergency response unit. This prompt notification enables a swift investigation and response to ensure safety.
[015] The real-time data from the cameras and sensors monitoring vehicle movement in the underpass and tunnel is continuously analysed and processed. The system captures key information such as vehicle type, number plate, and any delays or anomalies that may suggest issues like waterlogging. This data is then uploaded to a cloud-based platform, enabling remote access and storage for further analysis. The cloud platform integrates this real-time information with geographic mapping systems, such as Google Maps, to provide live updates on the condition of the underpass and tunnel. If flooding is detected, the system marks the affected areas on the map and sends alerts to drivers, helping them avoid the flooded underpass and tunnel. , C , Claims:1. Claim 1: A system for detecting and monitoring waterlogging in underpasses and tunnels, comprising:
• a network of IoT sensors installed in strategic locations within the underpass and tunnel to continuously measure water depth and detect real-time water levels.
• a real-time alert mechanism that activates when water levels exceed a predefined safety threshold.
• an automated gate control system that restricts vehicle access when unsafe water levels are detected, thereby preventing potential accidents.
2. The system of claim 1, wherein the IoT sensors are further configured to activate drainage systems and pumps automatically once the water levels reach a critical point, ensuring that excessive water accumulation is prevented and facilitating efficient water clearance to maintain safe traffic conditions.
3. Claim 2: A vehicle detection and monitoring system, comprising:
• cameras positioned at the entry and exit points of the underpass and tunnel to capture high-resolution images of vehicles.
• a deep learning-based image processing system for classifying vehicles into categories, including buses, trucks, and small vehicles.
• a time-monitoring feature to track the duration of a vehicle's passage through the underpass and tunnel.
• an alert system that notifies rescue teams when a vehicle does not exit the underpass and tunnel within a predefined period, indicating a potential emergency or waterlogging.
4. The system of claim 2, wherein the vehicle classification and monitoring system is integrated with an anomaly detection system that flags vehicles based on their delayed movement, triggering alerts to rescue teams for a rapid response.
5. Claim 3: A cloud-based data analysis and alert system, comprising:
• real-time uploading and processing of data collected from IoT sensors and vehicle monitoring systems in the and tunnel.
• integration with geographic mapping platforms, such as Google Maps, to mark waterlogged areas in real-time.
• an alert system to inform drivers of waterlogged or hazardous conditions in the underpass and tunnel, allowing them to avoid the area and take alternative routes.
6. The system of claim 3, wherein the cloud-based platform is configured to store historical data for future analysis, enabling predictive maintenance of the underpass and tunnel infrastructure and improving the accuracy of the system over time.

Documents

NameDate
202441088791-COMPLETE SPECIFICATION [16-11-2024(online)].pdf16/11/2024
202441088791-DRAWINGS [16-11-2024(online)].pdf16/11/2024
202441088791-FORM 1 [16-11-2024(online)].pdf16/11/2024
202441088791-FORM 18 [16-11-2024(online)].pdf16/11/2024
202441088791-FORM-9 [16-11-2024(online)].pdf16/11/2024
202441088791-REQUEST FOR EARLY PUBLICATION(FORM-9) [16-11-2024(online)].pdf16/11/2024
202441088791-REQUEST FOR EXAMINATION (FORM-18) [16-11-2024(online)].pdf16/11/2024

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