scholarly journals On-Road Driver Monitoring System Based on a Solar-Powered In-Vehicle Embedded Platform

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Yen-Lin Chen ◽  
Chao-Wei Yu ◽  
Zi-Jie Chien ◽  
Chin-Hsuan Liu ◽  
Hsin-Han Chiang
Keyword(s):  
Solar Cells ◽  
Embedded System ◽  
Monitoring System ◽  
Driving Safety ◽  
Detection Accuracy ◽  
Eye Detection ◽  
Electric Cars ◽  
Vehicle System ◽  
Driver Monitoring ◽  
Solar Powered

This study presents an on-road driver monitoring system, which is implemented on a stand-alone in-vehicle embedded system and driven by effective solar cells. The driver monitoring function is performed by an efficient eye detection technique. Through the driver’s eye movements captured from the camera, the attention states of the driver can be determined and any fatigue states can be avoided. This driver monitoring technique is implemented on a low-power embedded in-vehicle platform. Besides, this study also proposed monitoring machinery that can detect the brightness around the car to effectively determine whether this in-vehicle system is driven by the solar cells or by the vehicle battery. On sunny days, the in-vehicle system can be powered by solar cell in places without the vehicle battery. While in the evenings or on rainy days, the ambient solar brightness is insufficient, and the system is powered by the vehicle battery. The proposed system was tested under the conditions that the solar irradiance is 10 to 113 W/m2and solar energy and brightness at 10 to 170. From the testing results, when the outside solar radiation is high, the brightness of the inside of the car is increased, and the eye detection accuracy can also increase as well. Therefore, this solar powered driver monitoring system can be efficiently applied to electric cars to save energy consumption and promote the driving safety.

Driver inattention monitoring system based on multimodal fusion with visual cues to improve driving safety

2016 ◽  
Vol 40 (3) ◽  
pp. 885-895 ◽  
Author(s):  
Xuanpeng Li ◽  
Emmanuel Seignez
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Visual Cues ◽  
Real Life ◽  
Multimodal Fusion ◽  
Driving Safety ◽  
Driver Drowsiness ◽  
Driver Monitoring ◽  
Driver Inattention ◽  
Multi Level

Driver inattention, either driver drowsiness or distraction, is a major contributor to serious traffic crashes. In general, most research on this topic studies driver drowsiness and distraction separately, and is often conducted in a well-controlled, simulated environment. By considering the reliability and flexibility of real-time driver monitoring systems, it is possible to evaluate driver inattention by the fusion of multiple selected cues in real life scenarios. This paper presents a real-time, visual-cue-based driver monitoring system, which can track both multi-level driver drowsiness and distraction simultaneously. A set of visual cues are adopted via analysis of drivers’ physical behaviour and driving performance. Driver drowsiness is evaluated using a multi-level scale, by applying evidence theory. Additionally, a general framework of extensive hierarchical combinations is used to generate a probabilistic evaluation of driving risk in real time. This driver inattention monitoring system with multimodal fusion has been proven to improve the accuracy of risk evaluation and reduce the rate of false alarms, and acceptance of the system is recommended.

Integrated Rear-view Mirror for Driver Monitoring System

2006 ◽  
Author(s):  
Koji Okuda ◽  
Michimasa Itoh ◽  
Bunji Inagaki
Keyword(s):  
Monitoring System ◽  
Rear View Mirror ◽  
Driver Monitoring

EFFICIENT QRS COMPLEX DETECTION ALGORITHM IMPLEMENTATION ON SOC-BASED EMBEDDED SYSTEM

2016 ◽  
Vol 78 (7-5) ◽  
Author(s):  
Muhammad Amin Hashim ◽  
Yuan Wen Hau ◽  
Rabia Baktheri
Keyword(s):  
Embedded System ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Qrs Complex ◽  
Qrs Detection ◽  
Qrs Complex Detection ◽  
Moving Windows ◽  
Field Programmable ◽  
Complex Detection ◽  
On Chip

This paper studies two different Electrocardiography (ECG) preprocessing algorithms, namely Pan and Tompkins (PT) and Derivative Based (DB) algorithm, which is crucial of QRS complex detection in cardiovascular disease detection. Both algorithms are compared in terms of QRS detection accuracy and computation timing performance, with implementation on System-on-Chip (SoC) based embedded system that prototype on Altera DE2-115 Field Programmable Gate Array (FPGA) platform as embedded software. Both algorithms are tested with 30 minutes ECG data from each of 48 different patient records obtain from MIT-BIH arrhythmia database. Results show that PT algorithm achieve 98.15% accuracy with 56.33 seconds computation while DB algorithm achieve 96.74% with only 22.14 seconds processing time. Based on the study, an optimized PT algorithm with improvement on Moving Windows Integrator (MWI) has been proposed to accelerate its computation. Result shows that the proposed optimized Moving Windows Integrator algorithm achieves 9.5 times speed up than original MWI while retaining its QRS detection accuracy. 

scholarly journals Development of Solar-Powered of Sensors Based Smart Waste Monitoring System

2021 ◽  
Vol 12 (5) ◽  
pp. 580-586
Author(s):  
Polaiah Bojja, Pamula Raja Kumari, A.Nagavardhan N.Dinesh, M.Gopla D Anirudh
Keyword(s):  
Waste Management ◽  
Monitoring System ◽  
Smart City ◽  
Waste Treatment ◽  
Smart Cities ◽  
Municipal Waste ◽  
Waste Collection ◽  
Solar Powered ◽  
Analyze Data

Dustbins (or Garbage Bins, Trash Cans, whatever you name them) are small containers of plastic or metal used on a temporary basis to store trash (or waste). They are also used for the collection of waste in houses, workplaces, highways, parks, etc. Littering is a major crime in some countries, and public waste bins are also the only way to dispose of small waste. Usually, using different bins for handling wet or dry, recyclable or non-recyclable waste is a common practice. From an ETS perspective, smart waste collection can help municipalities and private waste management companies avoid the need for collection sites, waste disposal facilities and waste treatment plants. As communities increasingly rely on smart city technology to improve, among other things, the quality of life of their residents and the environment, city leaders recognize that smart waste management can also help them achieve sustainability goals such as zero waste and improve services to residents, while improving service to residents. As an example, Development of Some solar-powered bins and recycling bins are already equipped with sensors that analyze data on what is disposed of or recycled and notify collectors when the bin is too full and needs to be picked up. These developed Smart waste management solutions use sensors placed in waste bins to measure levels, notify municipal waste collection services, when the bins are ready to be emptied, and also notify municipal waste collection with a ton has been emptied. Therefore, the solar-powered of sensors based smart waste monitoring system is more and more useful to the current smart cities policies under the smart city project works.

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