Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3
Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3
Blockchain-Enabled Federated Learning on Kubernetes for Air Quality Prediction Applications
Volume-3 | Issue-3
Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4
Hybrid Parallel Image Processing Algorithm for Binary Images with Image Thinning Technique
Volume-3 | Issue-3
Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4
QoS-aware Virtual Machine (VM) for Optimal Resource Utilization and Energy Conservation
Volume-3 | Issue-3
Probabilistic Neural Network based Managing Algorithm for Building Automation System
Volume-3 | Issue-4
Fusion based Feature Extraction Analysis of ECG Signal Interpretation - A Systematic Approach
Volume-3 | Issue-1
Multi-scale CNN Approach for Accurate Detection of Underwater Static Fish Image
Volume-3 | Issue-3
Real Time Anomaly Detection Techniques Using PySpark Frame Work
Volume-2 | Issue-1
Deniable Authentication Encryption for Privacy Protection using Blockchain
Volume-3 | Issue-3
Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis
Volume-3 | Issue-4
Sentiment Analysis of Nepali COVID19 Tweets Using NB, SVM AND LSTM
Volume-3 | Issue-3
Audio Tagging Using CNN Based Audio Neural Networks for Massive Data Processing
Volume-3 | Issue-4
Frontiers of AI beyond 2030: Novel Perspectives
Volume-4 | Issue-4
Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare
Volume-3 | Issue-4
Early Stage Detection of Crack in Glasses by Hybrid CNN Transformation Approach
Volume-3 | Issue-4
ARTIFICIAL INTELLIGENCE APPLICATION IN SMART WAREHOUSING ENVIRONMENT FOR AUTOMATED LOGISTICS
Volume-1 | Issue-2
Deep Convolution Neural Network Model for Credit-Card Fraud Detection and Alert
Volume-3 | Issue-2
Volume - 3 | Issue - 2 | june 2021
Published
23 June, 2021
One of the many challenges that the world faces is traffic hazard. The major cause of this traffic risk is the presence of a huge number of vehicles on the road. As a result, it generates the most challenging issues, leading to an increase in the death toll due to road accidents that occur throughout the world. As a result, it necessitates the need to provide adequate transportation facilities, which will reduce the number of collisions and save human lives. The GPS, GSM, accelerometer, Arduino UNO technology, and vibration sensor are used to design and develop a vehicle accident detection model. The proposed approach is classified into three stages to prevent and detect the vehicular accidents. At the detection stage, a vibration sensor will be utilized to determine the position of the accident and to alert the user by sending SMS via the GSM module, which will include the user's data stored in Android applications. This data will be taken from the GPS module. The second phase occurs when moderate accidents occur and in such situation, the location will be detected by using a GPS module. After that, the nearby hospital receives a message about the accidents and accordingly they provide services to the accidents. At the same time, after detecting the location, a patient receives a message from the hospital urging them to take precautions.
KeywordsIoT embedded systems application safety awareness GSM module GPS module
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