scholarly journals Public Opinion Analysis of Road Accidents & Review of Conventional and Combinational Driver Safety Methodologies with SelfLearning Algorithms

2021 ◽  
Vol 12 (2) ◽  
pp. 3245-3260
Author(s):  
Tamilarasi A, Et. al.
Keyword(s):  
Public Opinion ◽  
Tamil Nadu ◽  
Detection System ◽  
Detection Algorithm ◽  
Driver Assistance ◽  
Accurate Analysis ◽  
Fitting Algorithm ◽  
Tamil Nadu State ◽  
Curvature Estimation ◽  
Accident Detection

Advanced driver assistance and accident detection system is significantlyneeded to ensure safety for drivers. Drowsiness detection, collision detection and various driver alert systems have penetrated into market with an aim to provide higher security for driver but due to population of vehicle and modification in structure of roads these system fails to answer safety problems that results in severe accidents.In this paper we provide accurate analysis of past recorded accidents in Tamil Nadu state and analysis of public opinion on Accident detection system is carried out using 1004 licensed persons under different ages in three cities (Coimbatore, Erode and Nilgiris) by focusing the major 10 parameters carrying 48 Questions. Findings and implications of this analysis is also discussed in this article. A thorough analysis of recent techniques that are used for AAD (Automatic Accident Detection) and road safety programmes that resolve the pre and post cautionary concerns of accidents in developing countries is addressed with the review of most 4 influencing algorithms in ITS for AAD.. 1 Vehicle Detection using Wheel arc Counter Detection Algorithm, 2 Enhancement of V2X Communication using Multi-RAT,3Road Curvature Estimation using Circle Fitting Algorithm and4Driver Safety Systemis discussed in this paper. To understand recent computational challenges and extended areas of research in ITS, anhybrid approach of CNN with VANETs for accident detection has been suggested to enumerate the obtained accidental information.

scholarly journals Vision-Based Lane Line Detection System

2021 ◽  
Vol 09 (06) ◽  
Author(s):  
Poorna Vishwanth ◽  
Keyword(s):  
Automobile Industry ◽  
Detection System ◽  
Warning System ◽  
Vehicle Detection ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Line Detection ◽  
Vertical Edge ◽  
Horizontal Edge ◽  
Driver Assistance

Since the 1990s, the rising key issue of the automobile industry is self-driving or driverless vehicles. Apparently, one of the most important challenges for smart self-driving cars comprises lane-detecting and lane-tracking capability to ensure safety and also decrease vehicle accidents for driver assistance systems. Since road lane detection is one of the most challenging tasks, driverless vehicles must learn to observe the road from a visual perspective in order to achieve automatic driving. Most of the research Works done so far can only detect the lanes or vehicles separately. However, in this paper, we propose a method to combine lane information and vehicle/obstacle information that can support the driver assistance system, driver warning system or the lane change assistant system so that it enhances the quality of results. For the lane changing system, the system detects or tracks the lane lines and detects the vehicles on all sides of a test vehicle. In lane detection, line detection algorithms such as the Canny Edge detection algorithm are used to detect the lane edges. Kalman filter will be used to track the vehicle detected from the vehicle detection algorithm. For vehicle detection, we use Otsu’s thresholding, horizontal edge filtering and vertical edge. The vertical edge filter and the Otsu’s thresholding are used to detect the vehicles on all sides of the test vehicles, then the horizontal edge is used to verify the vehicles detected.

A Study on Job Satisfaction among Tamil Nadu State Transport Corporation (TNSTC) Employees at Tiruvarur Branch

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 230-242
Author(s):  
M. Ganesan, K ◽  
K. Veerakumar ◽  
N. R Vembu ◽  
Dr. M. K Durgamani ◽  
Dr. Renuka
Keyword(s):  
Job Satisfaction ◽  
Job Stress ◽  
Tamil Nadu ◽  
Heavy Traffic ◽  
Road Transportation ◽  
The Road ◽  
Tamil Nadu State ◽  
On The Road ◽  
Day By Day ◽  
Labour Turnover

Job satisfaction is an important factor for employees working in formal and informal sector. The job is small or big, permanent or temporary, risky or non-risky, job satisfaction is important. It is the mental feeling which drives the employees to excel. Job satisfaction is a combination of psychological, physiological and environmental circumstances. A satisfied employee is a contented and happy human being. The labour turnover depends upon job satisfaction. Even highly paid employees quit the job when they are not satisfied with the job. Road transportation in Tamilnadu is growing day by day. Job stress in the road transportation is very high due to increase in number of vehicle playing on the road and heavy traffic. The drivers and conductors working in public transport corporation are suffering from high job stress. If drivers and conductors are not satisfied with their job which leads to mental stresses and affects the productivity and also creates accidents. In this present study the researchers made an attempt to study the level of job satisfaction among the drivers and conductors who are working in the Tamilnadu State Transport Corporation (TNSTC). The study reveals the expectations of drivers and conductors working in TNSTC with regards to the attributes like salary, promotion and fringe benefits etc., are satisfactory and not detrimental. 

Implementation of Automatic vehicle accident detection system using Zigbee

2017 ◽  
Vol 1 (1) ◽  
pp. 1-6
Author(s):  
Ginne Rani ◽  
◽  
Aman Dhingya ◽  
Ankur Gupta ◽  
Sagar Kumar ◽  
...  
Keyword(s):  
Detection System ◽  
Vehicle Accident ◽  
Accident Detection

scholarly journals Maternal Vitamin B12 Status and Risk of Cleft Lip and Cleft Palate Birth Defects in Tamil Nadu State, India

2021 ◽  
Vol 58 (5) ◽  
pp. 567-576
Author(s):  
Ronald G. Munger ◽  
Rajarajeswari Kuppuswamy ◽  
Jyotsna Murthy ◽  
Kalpana Balakrishnan ◽  
Gurusamy Thangavel ◽  
...  
Keyword(s):  
Cleft Palate ◽  
Tamil Nadu ◽  
Cleft Lip ◽  
Maternal Nutrition ◽  
Case Control ◽  
Vitamin B ◽  
Plasma Vitamin ◽  
Maternal Vitamin ◽  
Increased Risk ◽  
Tamil Nadu State

Background and Objective: The causal role of maternal nutrition in orofacial clefts is uncertain. We tested hypotheses that low maternal vitamin B12 and low folate status are each associated with an increased risk of isolated cleft lip with or without cleft palate (CL±P) in a case–control study in Tamil Nadu state, India. Methods: Case-mothers of CL±P children (n = 47) and control-mothers of unaffected children (n = 50) were recruited an average of 1.4 years after birth of the index child and plasma vitamin B12, methylmalonic acid (MMA), total homocysteine (tHcy), and folate were measured at that time. Logistic regression analyses estimated associations between nutrient biomarkers and case–control status. Results: Odds ratios (ORs) contrasting biomarker levels showed associations between case-mothers and low versus high plasma vitamin B12 (OR = 2.48, 95% CI, 1.02-6.01) and high versus low plasma MMA, an indicator of poor B12 status (OR = 3.65 95% CI, 1.21-11.05). Case–control status was not consistently associated with folate or tHcy levels. Low vitamin B12 status, when defined by a combination of both plasma vitamin B12 and MMA levels, had an even stronger association with case-mothers (OR = 6.54, 95% CI, 1.33-32.09). Conclusions: Mothers of CL±P children in southern India were 6.5 times more likely to have poor vitamin B12 status, defined by multiple biomarkers, compared to control-mothers. Further studies in populations with diverse nutritional backgrounds are required to determine whether poor maternal vitamin B12 or folate levels or their interactions are causally related to CL±P.

scholarly journals Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1081
Author(s):  
Tamon Miyake ◽  
Shintaro Yamamoto ◽  
Satoshi Hosono ◽  
Satoshi Funabashi ◽  
Zhengxue Cheng ◽  
...  
Keyword(s):  
Learning Algorithm ◽  
Detection System ◽  
Calibration Method ◽  
Detection Algorithm ◽  
Video Data ◽  
Detection Accuracy ◽  
Phase Detection ◽  
Gait Phase ◽  
Logistic Regression Algorithm ◽  
Short Time

Gait phase detection, which detects foot-contact and foot-off states during walking, is important for various applications, such as synchronous robotic assistance and health monitoring. Gait phase detection systems have been proposed with various wearable devices, sensing inertial, electromyography, or force myography information. In this paper, we present a novel gait phase detection system with static standing-based calibration using muscle deformation information. The gait phase detection algorithm can be calibrated within a short time using muscle deformation data by standing in several postures; it is not necessary to collect data while walking for calibration. A logistic regression algorithm is used as the machine learning algorithm, and the probability output is adjusted based on the angular velocity of the sensor. An experiment is performed with 10 subjects, and the detection accuracy of foot-contact and foot-off states is evaluated using video data for each subject. The median accuracy is approximately 90% during walking based on calibration for 60 s, which shows the feasibility of the static standing-based calibration method using muscle deformation information for foot-contact and foot-off state detection.

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