scholarly journals Micro Controller Based Smart Helmet by Ir Motion Sensors

2019 ◽  
Vol 8 (6) ◽  
pp. 1850-1853
Keyword(s):  
Road Accident ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Road Accidents ◽  
Rf Transmitter ◽  
Ir Sensor ◽  
Alcohol Sensor ◽  
Receiver Unit ◽  
Drunken Driving

Road accident is an unintended incident which is responsible for deaths of people worldwide. According to National Crime Records Bureau (NCRB), more than 1, 35,000 people die every year annually in Indian road accidents. The most significant cause is drunken driving and not wearing helmets while driving. The main objective here is to eradicate drunken driving and helmetless driving. In this regard, an attempt has been made by using microcontroller assisted RF transmitter and receiver unit. The IR sensor detects the presence of helmet on the head. MQ3 alcohol sensor detects the alcohol level. The comparator analyse the values and gives command to relay circuit. Thus the starting of two wheelers is controlled by the application of sensors. In addition to this, a motion sensor has also been incorporated to inform the driver about the presence of nearby vehicles.

scholarly journals Quantifying Habitual Physical Activity and Sedentariness in Older Adults—Different Outcomes of Two Simultaneously Body-Worn Motion Sensor Approaches and a Self-Estimation

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1877
Author(s):  
Rieke Trumpf ◽  
Wiebren Zijlstra ◽  
Peter Haussermann ◽  
Tim Fleiner
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Community Dwelling ◽  
Habitual Physical Activity ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Healthy Older Adults ◽  
Lower Back ◽  
Hybrid Motion ◽  
Accurate Quantification

Applicable and accurate assessment methods are required for a clinically relevant quantification of habitual physical activity (PA) levels and sedentariness in older adults. The aim of this study is to compare habitual PA and sedentariness, as assessed with (1) a wrist-worn actigraph, (2) a hybrid motion sensor attached to the lower back, and (3) a self-estimation based on a questionnaire. Over the course of one week, PA of 58 community-dwelling subjectively healthy older adults was recorded. The results indicate that actigraphy overestimates the PA levels in older adults, whereas sedentariness is underestimated when compared to the hybrid motion sensor approach. Significantly longer durations (hh:mm/day) for all PA intensities were assessed with the actigraph (light: 04:19; moderate to vigorous: 05:08) when compared to the durations (hh:mm/day) that were assessed with the hybrid motion sensor (light: 01:24; moderate to vigorous: 02:21) and the self-estimated durations (hh:mm/day) (light: 02:33; moderate to vigorous: 03:04). Actigraphy-assessed durations of sedentariness (14:32 hh:mm/day) were significantly shorter when compared to the durations assessed with the hybrid motion sensor (20:15 hh:mm/day). Self-estimated duration of light intensity was significantly shorter when compared to the results of the hybrid motion sensor. The results of the present study highlight the importance of an accurate quantification of habitual PA levels and sedentariness in older adults. The use of hybrid motion sensors can offer important insights into the PA levels and PA types (e.g., sitting, lying) and it can increase the knowledge about mobility-related PA and patterns of sedentariness, while actigraphy appears to be not recommendable for this purpose.

scholarly journals Assessment of logistical support for road maintenance to manage road accidents in Vhembe district municipalities

2019 ◽  
Vol 11 (3) ◽  
Author(s):  
Peter Bikam
Keyword(s):  
Service Providers ◽  
Road Accident ◽  
Motor Vehicles ◽  
Road Maintenance ◽  
Road Accidents ◽  
Deficit Model ◽  
Technology Innovations ◽  
Operations And Maintenance ◽  
Materials Used ◽  
Vhembe District

This article discusses the problems of logistical support for road maintenance to manage road accidents in Vhembe district municipalities. A budget deficit model was used to explain the level of inadequate logistics support to manage operations and maintenance of municipal roads as a preventative measure against road accident and disaster risks. A hypothetical road maintenance deficit model informed by current literature on road maintenance was used to explain how cost of road maintenance increases exponentially if initial maintenance was not undertaken when the facility was newly constructed to draw the link between road maintenance and the risk of road accidents. Inadequate logistical support to address road maintenance backlogs in Vhembe district municipalities has been on the increase over the last 10 years. Current studies show that inadequate road maintenance can lead to the development of potholes – a major cause of road accidents and damages to motor vehicles. Literature on logistics support emphasises a comprehensive approach to road maintenance to provide a balance between funding, routine maintenance, quality of materials used for maintenance, use of stipulated specifications, the required maintenance technology, innovations and employment of qualified service providers to ensure quality roads and reduction of accidents on municipal roads.

Reverse Electrowetting-on-Dielectric Energy Harvesting Integrated With Charge Amplifier and Rectifier for Self-Powered Motion Sensors

2020 ◽  
Author(s):  
Pashupati R. Adhikari ◽  
Nishat T. Tasneem ◽  
Dipon K. Biswas ◽  
Russell C. Reid ◽  
Ifana Mahbub
Keyword(s):  
Energy Harvester ◽  
Schottky Diodes ◽  
Boost Converter ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Frequency Range ◽  
Charge Amplifier ◽  
Electrowetting On Dielectric ◽  
Dc Voltage ◽  
Self Powered

Abstract This paper presents a reverse electrowetting-on-dielectric (REWOD) energy harvester integrated with rectifier, boost converter, and charge amplifier that is, without bias voltage, capable of powering wearable sensors for monitoring human health in real-time. REWOD has been demonstrated to effectively generate electrical current at a low frequency range (< 3 Hz), which is the frequency range for various human activities such as walking, running, etc. However, the current generated from the REWOD without external bias source is insufficient to power such motion sensors. In this work, to eventually implement a fully self-powered motion sensor, we demonstrate a novel bias-free REWOD AC generation and then rectify, boost, and amplify the signal using commercial components. The unconditioned REWOD output of 95–240 mV AC is generated using a 50 μL droplet of 0.5M NaCl electrolyte and 2.5 mm of electrode displacement from an oscillation frequency range of 1–3 Hz. A seven-stage rectifier using Schottky diodes having a forward voltage drop of 135–240 mV and a forward current of 1 mA converts the generated AC signal to DC voltage. ∼3 V DC is measured at the boost converter output, proving the system could function as a self-powered motion sensor. Additionally, a linear relationship of output DC voltage with respect to frequency and displacement demonstrates the potential of this REWOD energy harvester to function as a self-powered wearable motion sensor.

scholarly journals Road Transport Accidents in Nigeria and the Role of Automotive Active Safety System

2016 ◽  
Vol 11 (1) ◽  
pp. 49-54
Author(s):  
Olasunkanmi Oriola Akinyemi ◽  
Hezekiah O Adeyemi ◽  
Olusegun Jinadu
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Transportation Network ◽  
Road Transport ◽  
Road Accident ◽  
Active Safety ◽  
Road Accidents ◽  
Road Transportation ◽  
Road Traffic Safety

Abstract Analysis of road traffic accidents revealed that most accidents are as a result of drivers’ errors. Over the years, active safety systems (ASS) were devised in vehicle to reduce the high level of road accidents, caused by human errors, leading to death and injuries. This study however evaluated the impacts of ASS inclusions into vehicles in Nigeria road transportation network. The objectives was to measure how ASS contributed to making driving safer and enhanced transport safety. Road accident data were collected, for a period of eleven years, from Lagos State Ministry of Economic Planning and Budget, Central Office of Statistics. Quantitative analysis of the retrospective accident was conducted by computing the proportion of yearly number of vehicles involved in road accident to the total number of vehicles for each year. Results of the analysis showed that the proportion of vehicles involved in road accidents decreased from 16 in 1996 to 0.89 in 2006, the injured persons reduced from 15.58 in 1998 to 0.3 in 2006 and the death rate diminished from 4.45 in 1998 to 0.1 in 2006. These represented 94.4 %, 95 % and 95 % improvement respectively on road traffic safety. It can therefore be concluded that the inclusions of ASS into design of modern vehicles had improved road safety in Nigeria automotive industry.

scholarly journals Application of IOT for Human Safety on Road

2021 ◽  
Vol 12 (2) ◽  
Author(s):  
Tripura Pidikiti , Et. al.
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Infrared Sensor ◽  
Road Accidents ◽  
Emergency Center ◽  
Global Positioning ◽  
Prevention System ◽  
Alcohol Sensor ◽  
Two Wheeler ◽  
Accident Detection

Two wheelers (motor bikes) are most used easy and economic means of transportation and it also has become unsafe because of the tremendous increase of road accidents. When two-wheeler met with an accident, it is difficult to spot the neighborhood of the accident and mammoth loss occurs due to time factor. This paper presents Internet of Things based accident detection and prevention system. This is a novel system divided into four parts: first to identify the accident to send signal to emergency center along with location using Arduino based Global Positioning System and Global System for Mobile Communication and remaining are to warn to prevent the accidents like an accelerometer to determine the velocity and tilt of the vehicle, Infrared sensor to detect any obstacles and an alcohol sensor.

scholarly journals Machine Learning Approaches to Traffic Accident Analysis and Hotspot Prediction

Computers ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 157
Author(s):  
Daniel Santos ◽  
José Saias ◽  
Paulo Quaresma ◽  
Vítor Beires Nogueira
Keyword(s):  
Machine Learning ◽  
Predictive Model ◽  
Road Accident ◽  
Influential Factors ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Economic Losses ◽  
Learning Approaches ◽  
Road Accidents ◽  
Accident Data

Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses. There are many factors that are responsible for causing road accidents. If these factors can be better understood and predicted, it might be possible to take measures to mitigate the damages and its severity. The purpose of this work is to identify these factors using accident data from 2016 to 2019 from the district of Setúbal, Portugal. This work aims at developing models that can select a set of influential factors that may be used to classify the severity of an accident, supporting an analysis on the accident data. In addition, this study also proposes a predictive model for future road accidents based on past data. Various machine learning approaches are used to create these models. Supervised machine learning methods such as decision trees (DT), random forests (RF), logistic regression (LR), and naive Bayes (NB) are used, as well as unsupervised machine learning techniques including DBSCAN and hierarchical clustering. Results show that a rule-based model using the C5.0 algorithm is capable of accurately detecting the most relevant factors describing a road accident severity. Further, the results of the predictive model suggests the RF model could be a useful tool for forecasting accident hotspots.

scholarly journals Assessing the Mobility of Elderly People in Domestic Smart Home Environments

2020 ◽  
Author(s):  
Björn Friedrich ◽  
Enno-Edzard Steen ◽  
Sebastian Fudickar ◽  
Andreas Hein
Keyword(s):  
Elderly People ◽  
Smart Home ◽  
Continuous Monitoring ◽  
Early Stage ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Physical Strength ◽  
Assessment Scores ◽  
Mobility Assessment ◽  
Smart Home Environments

A continuous monitoring of the physical strength and mobility of elderly people is important for maintaining their health and treating diseases at an early stage. However, frequent screenings by physicians are exceeding the logistic capacities. An alternate approach is the automatic and unobtrusive collection of functional measures by ambient sensors. In the current publication, we show the correlation among data of ambient motion sensors and the wellestablished mobility assessment Short-Physical-Performance-Battery and Tinetti. We use the average number of motion sensor events for correlation with the assessment scores. The evaluation on a real-world dataset shows a moderate to strong correlation with the scores of standardised geriatrics physical assessments.

scholarly journals TRAFFIC-RELATED MORTALITY IN MOLDOVA

2020 ◽  
pp. 140-147
Keyword(s):  
Life Expectancy ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accident ◽  
Road Accidents ◽  
Continuous Increase ◽  
Risk Of Death ◽  
Significant Difference ◽  
Related Mortality

This article analyses the mortality caused by road accidents in Moldova depending on the degree of involvement of pedestrians, cyclists, motorcyclists, drivers and passengers of transport units, depending on age and sex. Results suggest that traffic-related mortality in Moldova has shown an increased incidence among the young and working-age population, where a significant difference between males and females is observed. Among the youth, traffic-related deaths register between 10-27% of the overall mortality in both sexes. The risk exposure of dying in a traffic accident decreases with age and is less significant in the retired ages. During the years 1998-2015, avoidance of trafficrelated deaths would have assured an increase in life expectancy between 0.40-0.56 years in males, and 0.09-0.23 years in females. The continuous increase in the number of transport units on public roads, as well as in the number of hours spent in traffic, influences the degree of exposure to the risk of death or injury as a result of road traffic accidents. Trauma resulting from road accidents increases the incidence of premature mortality and disability among the population, which is reflected by the decrease of healthy life expectancy. It is ascertained that the road accident mortality requires a detailed and comprehensive analysis given the multitude of factors influencing deaths and injuries related to a traffic accident among the population. Thus, in order to improve road safety and reduce mortality incidence among traffic participants, a range of actions has to be implemented by the liable actors, including through the international experience.

scholarly journals Evaluation of Joint Motion Sensing Efficiency According to the Implementation Method of SWCNT-Coated Fabric Motion Sensor

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 284 ◽  
Author(s):  
Hyun-Seung Cho ◽  
Jin-Hee Yang ◽  
Jeong-Hwan Lee ◽  
Joo-Hyeon Lee
Keyword(s):  
Motion Sensor ◽  
Joint Motion ◽  
Motion Sensors ◽  
Motion Sensing ◽  
Piezoresistive Sensors ◽  
Piezoresistive Sensor ◽  
Acceleration Sensors ◽  
Flexion Extension ◽  
Joint Motions ◽  
Walled Carbon Nanotubes

The purpose of this study was to investigate the effects of the shape and attachment position of stretchable textile piezoresistive sensors coated with single-walled carbon nanotubes on their performance in measuring the joint movements of children. The requirements for fabric motion sensors suitable for children are also identified. The child subjects were instructed to wear integrated clothing with sensors of different shapes (rectangular and boat-shaped), attachment positions (at the knee and elbow joints or 4 cm below the joints). The change in voltage caused by the elongation and contraction of the fabric sensors was measured for the flexion-extension motions of the arms and legs at 60°/s (three measurements of 10 repetitions each for the 60° and 90° angles, for a total of 60 repetitions). Their reliability was verified by analyzing the agreement between the fabric motion sensors and attached acceleration sensors. The experimental results showed that the fabric motion sensor that can measure children’s arm and leg motions most effectively is the rectangular-shaped sensor attached 4 cm below the joint. In this study, we developed a textile piezoresistive sensor suitable for measuring the joint motion of children, and analyzed the shape and attachment position of the sensor on clothing suitable for motion sensing. We showed that it is possible to sense joint motions of the human body by using flexible fabric sensors integrated into clothing.

scholarly journals A Hierarchical Deep Fusion Framework for Egocentric Activity Recognition Using a Wearable Hybrid Sensor System

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 546 ◽  
Author(s):  
Haibin Yu ◽  
Guoxiong Pan ◽  
Mian Pan ◽  
Chong Li ◽  
Wenyan Jia ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Short Term Memory ◽  
Specific Activity ◽  
Negative Influence ◽  
Sensor System ◽  
Sensor Data ◽  
Motion Sensor ◽  
Motion Sensors ◽  
Motion State ◽  
Fusion Framework

Recently, egocentric activity recognition has attracted considerable attention in the pattern recognition and artificial intelligence communities because of its wide applicability in medical care, smart homes, and security monitoring. In this study, we developed and implemented a deep-learning-based hierarchical fusion framework for the recognition of egocentric activities of daily living (ADLs) in a wearable hybrid sensor system comprising motion sensors and cameras. Long short-term memory (LSTM) and a convolutional neural network are used to perform egocentric ADL recognition based on motion sensor data and photo streaming in different layers, respectively. The motion sensor data are used solely for activity classification according to motion state, while the photo stream is used for further specific activity recognition in the motion state groups. Thus, both motion sensor data and photo stream work in their most suitable classification mode to significantly reduce the negative influence of sensor differences on the fusion results. Experimental results show that the proposed method not only is more accurate than the existing direct fusion method (by up to 6%) but also avoids the time-consuming computation of optical flow in the existing method, which makes the proposed algorithm less complex and more suitable for practical application.

Sign in / Sign up

Export Citation Format

Share Document