scholarly journals An Agile Security System for Automobiles using IoT

2020 ◽  
Vol 9 (1) ◽  
pp. 1502-1504
Keyword(s):  
Embedded System ◽  
Liquid Crystal Display ◽  
Pressure Sensors ◽  
Security System ◽  
Image Processing Technique ◽  
Raspberry Pi ◽  
Processing Unit ◽  
Motion Sensors ◽  
Efficient System ◽  
Central Processing

Thieves are becoming smarter day-by-day which results in increase of looting of automobiles like scooters, cars and many other. To overcome this problem there is a crucial need for an effective system that diagnoses the vehicle theft. In this paper, an IoT based agile security system by using Raspberry Pi as the central processing unit of the entire system, a lightweight, cheap and efficient system is researched, built and explored. The Linux Embedded System gathers the data from Passive Infra-Red (PIR) motion sensors, pressure sensors, gas sensors, Global Positioning System (GPS), Pi camera, buzzer, and Liquid Crystal Display (LCD). The system has generally 2 modes. They are: Owner mode and Theft mode. If the system detects any intrusion in the vehicle it gives an alarm on detection, capture the image of the person by using image processing technique and identifies who is trying to unlock the vehicle and send coordinates of the vehicle when the intruder opens the vehicle door and starts moving the car, along with images of intruder to the owner by using a GSM module. By using GPS module, we can be to get the latitude and longitude of the vehicle remotely when the intruder has theft the vehicle.

scholarly journals GPU Accelerated real-time Melanoma Detection

2018 ◽  
Vol 7 (3) ◽  
pp. 1208
Author(s):  
Ajai Sunny Joseph ◽  
Elizabeth Isaac
Keyword(s):  
Real Time ◽  
Video Processing ◽  
Processing Technique ◽  
Video Data ◽  
Image Processing Technique ◽  
Processing Unit ◽  
Central Processing ◽  
Melanoma Detection ◽  
Real Time Analysis ◽  
Graphical Processing

Melanoma is recognized as one of the most dangerous type of skin cancer. A novel method to detect melanoma in real time with the help of Graphical Processing Unit (GPU) is proposed. Existing systems can process medical images and perform a diagnosis based on Image Processing technique and Artificial Intelligence. They are also able to perform video processing with the help of large hardware resources at the backend. This incurs significantly higher costs and space and are complex by both software and hardware. Graphical Processing Units have high processing capabilities compared to a Central Processing Unit of a system. Various approaches were used for implementing real time detection of Melanoma. The results and analysis based on various approaches and the best approach based on our study is discussed in this work. A performance analysis for the approaches on the basis of CPU and GPU environment is also discussed. The proposed system will perform real-time analysis of live medical video data and performs diagnosis. The system when implemented yielded an accuracy of 90.133% which is comparable to existing systems.  

scholarly journals Design and Power Management of a Secured Wireless Sensor System for Salton Sea Environmental Monitoring

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 544
Author(s):  
Kristian Diaz ◽  
Ying-Khai Teh
Keyword(s):  
Embedded System ◽  
Power Optimization ◽  
Finite Energy ◽  
Environmental Data ◽  
Salton Sea ◽  
Processing Unit ◽  
Energy Aware ◽  
Imperial Valley ◽  
Central Processing ◽  
Commercial Off The Shelf

An embedded system composed of commercial off the shelf (COTS) peripherals and microcontroller. The system will collect environmental data for Salton Sea, Imperial Valley, California in order to understand the development of environmental and health hazards. Power analysis of each system features (i.e. Central Processing Unit (CPU) core, Input/Output (I/O) buses, and peripheral (temperature, humidity, and optical dust sensor) are studied. Software-based power optimization utilizes the power information with hardware-assisted power gating to control system features. The control of these features extends system uptime in a field deployed finite energy scenario. The proposed power optimization algorithm can collect more data by increasing system up time when compared to a Low Power Energy Aware Processing (LEAP) approach. Lastly, the 128 bit Advanced Encryption Standard (AES) algorithm is applied on the collected data using various parameters. A hidden peripheral requirement that must be considered during design are also noted to impact the efficacy of this method.

scholarly journals Energy Efficiency of Machine Learning in Embedded Systems Using Neuromorphic Hardware

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1069
Author(s):  
Minseon Kang ◽  
Yongseok Lee ◽  
Moonju Park
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
Embedded Systems ◽  
Embedded System ◽  
Detection System ◽  
Processing Unit ◽  
Process Data ◽  
Central Processing ◽  
Neuromorphic Hardware ◽  
Multicore Cpu

Recently, the application of machine learning on embedded systems has drawn interest in both the research community and industry because embedded systems located at the edge can produce a faster response and reduce network load. However, software implementation of neural networks on Central Processing Units (CPUs) is considered infeasible in embedded systems due to limited power supply. To accelerate AI processing, the many-core Graphics Processing Unit (GPU) has been a preferred device to the CPU. However, its energy efficiency is not still considered to be good enough for embedded systems. Among other approaches for machine learning on embedded systems, neuromorphic processing chips are expected to be less power-consuming and overcome the memory bottleneck. In this work, we implemented a pedestrian image detection system on an embedded device using a commercially available neuromorphic chip, NM500, which is based on NeuroMem technology. The NM500 processing time and the power consumption were measured as the number of chips was increased from one to seven, and they were compared to those of a multicore CPU system and a GPU-accelerated embedded system. The results show that NM500 is more efficient in terms of energy required to process data for both learning and classification than the GPU-accelerated system or the multicore CPU system. Additionally, limits and possible improvement of the current NM500 are identified based on the experimental results.

scholarly journals Raspberry Pi Based Home Surveillance System using SMTP

2020 ◽  
Vol 9 (1) ◽  
pp. 2792-2794
Keyword(s):  
Computer Vision ◽  
Surveillance System ◽  
High Efficiency ◽  
Raspberry Pi ◽  
Surveillance Systems ◽  
Processing Unit ◽  
Central Processing ◽  
Local Database ◽  
Python Language ◽  
Transfer Protocol

Different Technologies are emerging in the field of Home Surveillance now a days. Surveillance systems are being used to reduce man power and to increase security of a home. Technologies like Computer Vision and Internet of Things (IOT) are one of them. In this project a surveillance system has been implemented employing a single board computer i.e. Raspberry Pi 3 which will act like a central processing unit with the help of python language and a module named as Open Source Computer Vision(Open CV).To make it more automated a local database of authorized persons has been made. It will store the images of the different authorized persons who can enter in that security area. Camera will be always in surveillance mode and it will be searching for a face persistently. It’ll act as Computer Vision. This will lead to more accurate system with high efficiency. Therefore it’ll capture the image of the person automatically and compare it with the local database. In the case of match, door will be open automatically otherwise in the case of unauthorized person, system will send the image of the unauthorized person to owner of the home via SMTP(Simple Mail Transfer Protocol). A local library in Python - "smtplib" is being press into service to send messages. The smtplib module characterizes a SMTP customer meeting object that can be utilized to send messages to any Web machine with SMTP( Simple Mail Transfer Protocol). Also a webpage has been made with the help of apache server to store the images of unauthorized persons.

scholarly journals Software Optimisation of Lightweight Klein Encryption in IoT

2021 ◽  
Vol 4 (2) ◽  
pp. 55-68
Author(s):  
Seyed Ghorashi
Keyword(s):  
Block Cipher ◽  
Raspberry Pi ◽  
Processing Unit ◽  
Security Vulnerabilities ◽  
Original Algorithm ◽  
Central Processing ◽  
Python Language ◽  
Novel Method ◽  
Improved Performance ◽  
The Internet Of Things

The Internet of Things (IoT) and Wireless Sensor Network (WSN) devices are prone to security vulnerabilities, especially when they are resource-constrained. Lightweight cryptography is a promising encryption concept for IoT and WSN devices, that can mitigate these vulnerabilities. For example, Klein encryption is a lightweight block cipher, which has achieved popularity for the trade-off between performance and security. In this paper, we propose one novel method to enhance the efficiency of the Klein block cipher and the effects on the Central Processing Unit (CPU), memory usage, and processing time. Furthermore, we evaluate another approach on the performance of the Klein encryption iterations. These approaches were implemented in the Python language and ran on the Raspberry PI 3. We evaluated and analyzed the results of two modified encryption algorithms and confirmed that two enhancing techniques lead to significantly improved performance compared to the original algorithm

scholarly journals A Smart Watchdog - Intruder Detection System

2018 ◽  
Vol 7 (3.34) ◽  
pp. 231
Author(s):  
P Vasuki ◽  
Sesu Priya A ◽  
Soundarya R
Keyword(s):  
Embedded System ◽  
Detection System ◽  
Vital Role ◽  
Security System ◽  
Research Centre ◽  
Raspberry Pi ◽  
Security Systems ◽  
Security Controls ◽  
Dc Power ◽  
The Individual

In todays world, Security is a matter of great concern. Security controls play a vital role in protecting resources from espionage, sabotage, damage and theft. Our proposed system is to develop a security system with improved facilities, which tries to eliminate the limitations posed by the existing security systems. The current manual security system depends mostly on human involvement, which is prone to error, and the security is concentrated only at the front door which requires subjects cooperation. To solve these issues we have proposed a Smart Watchdog System. The system watches the environment, and if there is a human activity, the system captures it. The system automatically detects faces of the individual from the activity using firmware. We have planned to maintain the database of authorised inmates and workers of a place and verifies of every individual arriver. This feature enables the system to automatically recognises the unauthorised users and gives an alert when it encounters entry of unauthorised users even without the human assistance. The system also detects the unauthorised entry in the mass. The entire system is planned to be ported to Raspberry-Pi based Embedded System supported with DC power back up. This method can be employed in ladies hostels as well as to the secured places like the data centre, atomic research centre and military where the unauthorised entry is restricted.

Hardware Realization of Antifogging System

2017 ◽  
pp. 153-172
Author(s):  
Amruta Laxman Deshmukh ◽  
Satbir Singh ◽  
Balwinder Singh
Keyword(s):  
Embedded System ◽  
Low Power ◽  
Computer Model ◽  
Surveillance System ◽  
Low Cost ◽  
Model System ◽  
Raspberry Pi ◽  
Processing Unit ◽  
Matlab Code ◽  
Condensed Water

There are many reasons for invisibility of objects on road in daylight, majority of them are Fog (condensed water droplets in atmosphere), smog (soot particles in air). This reduced visibility is one of the prime factors responsible for accident of vehicles and disadvantage in surveillance system. This chapter takes account of a method that comprises of a complete embedded system for the process of restoring the captured foggy images. Use of a novel ‘Mean Channel Prior' algorithm for defogging is presented. Further detailed step by step explanation is given for hardware implementation of MATLAB code. Hardware consists of raspberry pi which is an ARM7 Quad Core processor based mini computer model. System serves as portable, low cost and low power processing unit with provision of interfacing a camera and a display screen.

scholarly journals Automatic Number Plate Recognition System using Raspberry Pi

2020 ◽  
Vol 9 (2) ◽  
pp. 1863-1865
Keyword(s):  
Computer Vision ◽  
Access Control ◽  
Embedded System ◽  
Recognition System ◽  
Binary Image ◽  
Security System ◽  
Raspberry Pi ◽  
Gray Scale

Automatic Number Plate Recognition System is an embedded system that acknowledges the vehicle number plate automatically. Automatic Number Plate Recognition is a technology for computer vision to find the number plates of vehicles from the images. There are many applications like parking, access control, security system, etc. In this paper, we propose a technique of implementing Automatic Number Plate Recognition System using Python and Open Computer Vision Library. The different stages that are involved in the implementation are conversion into gray scale, conversion into binary image, detects the edges of the image, to find the contours and finally displays the number plate of a vehicle

scholarly journals Security System to Prevent Tailgating Using Face Recognition and Ultrasonic Sensor

2020 ◽  
Vol 2 (5) ◽  
pp. 20-25
Author(s):  
Kannamma R ◽  
Bhargavi S ◽  
Bhavani Sree S ◽  
Mahalakshmi J
Keyword(s):  
Embedded System ◽  
Ultrasonic Sensor ◽  
Security System ◽  
Raspberry Pi ◽  
Security Guards ◽  
The People ◽  
Cloud Database ◽  
The One ◽  
Portable Embedded System ◽  
Python Package

Tailgating is the one where an employee holds the office door for others to enter into the building with one access. This leads to insecure where in the unknown person can also enters into the building with the access of the original employee. To overcome this, introducing security system that prevents tailgating that provides authentication, accuracy, flexibility and gives more convenience to the security guards. It is an embedded based system and built under the Linux environment. First the faces of all the people is captured and trained using OpenCV python package for the purpose of further experimentation in the future. In this Raspberry pi is used as a main controller along with camera which enables to access image processing with any portable embedded system. When the person enters near to the gate, the ultrasonic sensor starts to sense and triggers the camera which detects the person face and checks with the trained dataset using the Haar Cascading algorithm, if it matches the gate gets opened. If suppose the person enters the gate with other person with one access control, then again, the camera gets triggered to capture the unauthorized person face and sends the mail of the detected person to the concerned authority through firebase cloud database.

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