scholarly journals Integrate for car brake failure and engine overheat system

2020 ◽  
Vol 20 (3) ◽  
pp. 1299
Author(s):  
G. Subhashini ◽  
Anas Aiman Albanna ◽  
Raed Abdullah
Keyword(s):  
Warning System ◽  
Modern Technology ◽  
Sensor Data ◽  
Raspberry Pi ◽  
Monitoring And Control ◽  
Braking System ◽  
System A ◽  
Effective Delivery ◽  
Average Transmission ◽  
Web Platform

<span>One of the most important features in a car is its braking system and engine. The braking system enables the driver to control the speed of the vehicle when the need arises in order to protect the car, driver and other road users from accidents which might be fatal. The performance of the entire car also relies largely on the effective delivery and operation of the car engine whose ability to deliver the required performance is hinged on its temperature. In recent years a variety of IOT based monitoring and control systems have been explored in various areas of modern technology. This Final Year research project proposes the design and development of an IOT based vehicle brake failure and engine overheating system. The proposed system utilizes a network of sensors to monitor the temperature of the car engine, obstacles along the path of the car and the speed of the vehicle. The sensor data retrieved from the monitoring system is used by the control system consisting of a microcontroller to make decisive automatic decisions for the vehicle brake and failure system. A warning system consisting of LCD, Buzzer and LED has also been added into the system to warn the driver regarding the operation of the braking and engine overheating system. Two microcontrollers have been utilized for this research i.e. Arduino Uno for sensor data acquisition and processing and a Raspberry Pi microcontroller for purposes of sending the data wirelessly to a web platform. The web platform developed enables the user to remotely access real-time and past data from the system vehicle brake failure and engine overheating system. A variety of tests were conducted on the system to evaluate its performance whereby 95.4% accuracy was achieved in in terms of the ability of the car to effectively and automatically brake in the presence of obstacles and in terms of speed control. Testing done on the ability of the system to accurately monitor the engine temperature shows that its able to achieve 97.5% accuracy. The IOT system is able to transmit the sensor data retrieved from the system using both WIFI and mobile data whereby an average transmission time of 2.32 s and 4.33 s was recorded for each system respectively.</span>

Computer Vision and IoT based Automated Hydroponic Farms in Urban Areas- A Soilless Cultivation

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Computer Vision ◽  
Urban Areas ◽  
Modern Technology ◽  
Sensor Data ◽  
Raspberry Pi ◽  
Food Crisis ◽  
Agricultural Field ◽  
Rural Land ◽  
Soilless Cultivation ◽  
Potential Food

As the populace increments and characteristic assets decline, the capacity to serve humankind with an adequate measure of nourishment turns out to be progressively troublesome. The measure of rural land diminishes relatively to the expanding populace, along these lines the measure of nourishment delivered will diminish fundamentally, and will be lacking to serve the developing populace. The universal strategies for cultivating won't do the trick sooner. Thus, using modern technology and resources, a method of efficient farming must be introduced and employed in the agricultural field. This report introduces a method of efficient farming using hydroponics. The system is automated and uses sensor data to make decisions to benefit the crops being grown. The system runs on Raspberry PI and Arduino, and utilizes OpenCV. With our system we hope to solve the potential food crisis and give everyone access to fresh produce all year round.

A driver drowsiness and distraction warning system based on raspberry Pi 3 Kit

2019 ◽  
Vol 70 (3) ◽  
pp. 184-192
Author(s):  
Toan Dao Thanh ◽  
Vo Thien Linh
Keyword(s):  
Processing System ◽  
Warning System ◽  
Raspberry Pi ◽  
Data Set ◽  
Lower Lip ◽  
Driver Drowsiness ◽  
Image Sensing ◽  
The Face ◽  
The Common ◽  
University Laboratory

In this article, a system to detect driver drowsiness and distraction based on image sensing technique is created. With a camera used to observe the face of driver, the image processing system embedded in the Raspberry Pi 3 Kit will generate a warning sound when the driver shows drowsiness based on the eye-closed state or a yawn. To detect the closed eye state, we use the ratio of the distance between the eyelids and the ratio of the distance between the upper lip and the lower lip when yawning. A trained data set to extract 68 facial features and “frontal face detectors” in Dlib are utilized to determine the eyes and mouth positions needed to carry out identification. Experimental data from the tests of the system on Vietnamese volunteers in our University laboratory show that the system can detect at realtime the common driver states of “Normal”, “Close eyes”, “Yawn” or “Distraction”

Design and Simulation of Pedal Simulator in Brake by Wire System

2014 ◽  
Vol 556-562 ◽  
pp. 1358-1361 ◽  
Author(s):  
Wen Bo Zhu ◽  
Fen Zhu Ji ◽  
Xiao Xu Zhou
Keyword(s):  
Simulation Models ◽  
Control Algorithms ◽  
Brake Pedal ◽  
Braking System ◽  
Pedal Force ◽  
Performance Requirements ◽  
System A ◽  
Pedal Feel ◽  
And Control ◽  
Wire System

Wire of the brake pedal is not directly connected to the hydraulic environment in the braking By-wire system so the driver has no direct pedal feel. Then pedal simulator is an important part in the brake-by-wire system. A pedal force simulator was designed based on the traditional brake pedal curve of pedal force and pedal travel, AMESim and Matlab / Simulink were used as a platform to build simulation models and control algorithms. The simulation results show that the pedal stroke simulator and the control strategy meet the performance requirements of traditional braking system. It can be used in brake by wire system.

scholarly journals Machine Learning and Sensor Fusion for Estimating Continuous Energy Expenditure

AI Magazine ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 55 ◽  
Author(s):  
Nisarg Vyas ◽  
Jonathan Farringdon ◽  
David Andre ◽  
John Ivo Stivoric
Keyword(s):  
Machine Learning ◽  
Energy Expenditure ◽  
Sensor Data ◽  
Machine Learning Techniques ◽  
Sensor Technology ◽  
Health Goals ◽  
System A ◽  
Multi Sensor Data Fusion ◽  
Learning Techniques ◽  
Insight Into

In this article we provide insight into the BodyMedia FIT armband system — a wearable multi-sensor technology that continuously monitors physiological events related to energy expenditure for weight management using machine learning and data modeling methods. Since becoming commercially available in 2001, more than half a million users have used the system to track their physiological parameters and to achieve their individual health goals including weight-loss. We describe several challenges that arise in applying machine learning techniques to the health care domain and present various solutions utilized in the armband system. We demonstrate how machine learning and multi-sensor data fusion techniques are critical to the system’s success.

A Blockchain-Enabled Approach for Online Stream Sensor Data Protection in Cyber-Physical Manufacturing Systems

2021 ◽  
Author(s):  
Zhangyue Shi ◽  
Chenang Liu ◽  
Chen Kan ◽  
Wenmeng Tian ◽  
Yang Chen
Keyword(s):  
Information Technologies ◽  
Manufacturing Systems ◽  
Rapid Development ◽  
Data Access ◽  
Sensor Data ◽  
False Alarms ◽  
Monitoring And Control ◽  
Stream Data ◽  
Physical Security ◽  
And Control

Abstract With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality monitoring and control. However, the cyber-enabled environment may pose the collected online stream sensor data under high risks of cyber-physical attacks as well. Specifically, cyber-physical attacks could occur during the manufacturing process to maliciously tamper the sensor data, which could result in false alarms or failures of anomaly detection. In addition, the cyber-physical attacks may also illegally access the collected data without authorization and cause leakage of key information. Therefore, it becomes critical to develop an effective approach to protect online stream data from these attacks so that the cyber-physical security of the manufacturing systems could be assured. To achieve this goal, an integrative blockchain-enabled method, is proposed by leveraging both asymmetry encryption and camouflage techniques. A real-world case study that protects cyber-physical security of collected stream data in additive manufacturing is provided to demonstrate the effectiveness of the proposed method. The results demonstrate that malicious tampering could be detected in a relatively short time and the risk of unauthorized data access is significantly reduced as well.

Effectiveness of Truck Rollover Warning Systems

2001 ◽  
Vol 1779 (1) ◽  
pp. 134-140 ◽  
Author(s):  
Derek Baker ◽  
Rob Bushman ◽  
Curtis Berthelot
Keyword(s):  
North America ◽  
Warning System ◽  
Warning Systems ◽  
Commercial Vehicles ◽  
Decision Criteria ◽  
Warning Messages ◽  
System A ◽  
Different Types ◽  
Rollover Warning

Different types of intelligent rollover system deployed by road agencies across North America are investigated. The importance of weight is addressed for maximum effectiveness of rollover warning messages for commercial vehicles in a potential rollover situation on sharp curves or exit ramps. The type of information that may be used to activate a rollover is discussed to analyze the number of correctly warned vehicles compared with the number of false warnings generated by the rollover warning system. A case study of the effectiveness of an intelligent rollover system is presented. On the basis of this case study, it was found that speed-based rollover warning systems generated anywhere from 44 percent to 49 percent more false rollover warnings for commercial vehicles than did rollover warning systems that employed weight information in the rollover decision criteria.

scholarly journals Design of Early Warning System Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 66
Author(s):  
Gan Bo ◽  
Jin Shan
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Monitoring System ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Sensor Data ◽  
Landslide Monitoring ◽  
Remote Transmission ◽  
Sensor Data Acquisition

In order to solve the shortcomings of the landslide monitoring technology method, a set of landslides monitoring and early warning system is designed. It can achieve real-time sensor data acquisition, remote transmission and query display. In addition, aiming at the harsh environment of landslide monitoring and the performance requirements of the monitoring system, an improved minimum hop routing protocol is proposed. It can reduce network energy consumption, enhance network robustness, and improve node layout and networking flexibility. In order to realize the remote transmission of data, GPRS wireless communication is used to transmit monitoring data. Combined with remote monitoring center, real-time data display, query, preservation and landslide warning and prediction are realized. The results show that the sensor data acquisition system is accurate, the system is stable, and the node network is flexible. Therefore, the monitoring system has a good use value.

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