The Design and Implementation of Intelligent Community Monitoring System

2012 ◽  
Vol 463-464 ◽  
pp. 1701-1705
Author(s):  
Yu Lan Wang ◽  
Jian Xiong Wang ◽  
Yao Hui Li
Keyword(s):  
Data Storage ◽  
Research Work ◽  
Image Data ◽  
Moving Object ◽  
Video Image ◽  
Security Monitoring ◽  
Community Monitoring ◽  
Database Compression ◽  
Intelligent Community ◽  
Intelligent Security

This paper designs a stable, efficient and intelligent video surveillance system, which is based on the review and analysis of the domestic and internation. And it is related research work on the basis of the intelligent security monitoring. The system is used by the Web server and database server model, and it can detect the moving object in scene of monitor. Firstly this paper analyzes the structure of server system, it uses B/S, database, ActiveX technology and is completed finally. Secondly this paper realizes the video image data in bulk storage, read, update and maintenance by using the database. The bmp format will be converted to JPG format effectively to realize the image database compression. It is valued to the video image data storage and management. Finally, the accuracy and response time can be improved in moving object detection, which is based on background subtraction method

Design on Manufacturing Engineering Community Monitoring System Based on Wireless Sensor Network

2013 ◽  
Vol 340 ◽  
pp. 787-791
Author(s):  
Shu Wei
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Monitoring System ◽  
Living Environment ◽  
Wireless Sensor ◽  
Security Monitoring ◽  
Science Technology ◽  
Community Monitoring ◽  
Intelligent Community ◽  
Security Monitoring System

With the continuous development of economy and science technology, residential area shows the intelligent, humane and diverse development trends, residential security has been paid more and more attention. Community monitoring system provides security living environment for district residents, wireless sensor network technology provides an opportunity for security monitoring system and wireless network. On the foundation of wireless sensor network, constructing the intelligent community security monitoring system, the wireless communication node is designed, to carry out the study of the network communication protocol and algorithm. The experimental results show that this monitoring control system has low power consumption, functional diversity and communication stability, which is applicable to a variety of conditions of community security monitoring.

scholarly journals Enhanced Framework for Ensuring Privacy Preserving Image Retrieval in Cloud

2019 ◽  
Vol 8 (12) ◽  
pp. 2127-2132
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
Research Work ◽  
Image Data ◽  
Cloud Service ◽  
Sensitive Information ◽  
Cloud Platform ◽  
Privacy And Security ◽  
Computing Platform ◽  
Computing Platforms

Large scale of images data sets are being produced every day by various digital devices. Due to huge computational jobs make people seizure to cloud platforms for their efficient & economical reckoning resources. These computing platforms in which assets are provided as services of the internet. Sensitive information stored in cloud makes more challenging in data security and access control. Once data is uploaded to cloud-platform, the privacy and security of image-data fully depend and believe upon cloud service provider honesty. Our proposed work deals with securing image where high protections are applied on multimedia contents. This paper deals with studies security challenges algorithms lies in image at the time of constructing cloud platform. In this a new enhanced security technique investigated, includes secure by using computation and encryption, act as a security information guard for high secrecy in cloud platform data storage areas. In our research work, cipher-text image is created and performing encryption-decryption at User level. Data hiding and ECC (Elliptic curve cryptosystem) based watermarking technique at cloud computing platform.

Application of an image management system in microscopy

1992 ◽  
Vol 50 (2) ◽  
pp. 1052-1053
Author(s):  
Richard S. Chemock
Keyword(s):  
Data Storage ◽  
Cost Savings ◽  
Image Data ◽  
Analytical Techniques ◽  
Operational Mode ◽  
Fine Grained ◽  
Image Recording ◽  
Primary Output ◽  
Capacity Data ◽  
Image Management System

One of the most common tasks in a typical analysis lab is the recording of images. Many analytical techniques (TEM, SEM, and metallography for example) produce images as their primary output. Until recently, the most common method of recording images was by using film. Current PS/2R systems offer very large capacity data storage devices and high resolution displays, making it practical to work with analytical images on PS/2s, thereby sidestepping the traditional film and darkroom steps. This change in operational mode offers many benefits: cost savings, throughput, archiving and searching capabilities as well as direct incorporation of the image data into reports.The conventional way to record images involves film, either sheet film (with its associated wet chemistry) for TEM or PolaroidR film for SEM and light microscopy. Although film is inconvenient, it does have the highest quality of all available image recording techniques. The fine grained film used for TEM has a resolution that would exceed a 4096x4096x16 bit digital image.

D-buffer: irregular image data storage made practical

2013 ◽  
Vol 21 (1) ◽  
Author(s):  
J. Lipowski
Keyword(s):  
Data Storage ◽  
Image Data ◽  
Development Aid ◽  
Graphics Hardware ◽  
Address Space ◽  
Output Data ◽  
Frame Buffer ◽  
New Methods ◽  
Hardware Architectures ◽  
Depth Buffer

AbstractModern hardware accelerated graphics pipelines are designed to operate on data in a so called streaming model. To process the data in this model one needs to impose some restrictions on input and output argument’s (most frequently represented by a two-dimensional frame buffer) memory structure. The output data regularity is obvious when we consider rasterizing hardware architecture, which draws 3D polygons using depth buffer to resolve the visible surface problem. But recently the user’s needs surpass those restrictions with increasing frequency. In this work we formulate and present new methods of irregular frame buffer storage and ordering. The so called deque buffer (or D-buffer) allows us to decrease the amount of memory used for storage as well as the memory latency cost by using pixel data ordering. Our findings are confirmed by experimental results that measure the processing time, which is up to four times shorter, when compared with previous work by other authors. We also include a detailed description of algorithms used for D-buffer construction on the last three consumer-grade graphics hardware architectures, as a guide for other researchers and a development aid for practitioners. The only theoretical requirement imposed by our method is the use of memory model with linear address space.

scholarly journals Design and Implementation of Compressed Medical Data over an Authenticated Secured

2020 ◽  
Vol 9 (3) ◽  
pp. 1543-1548
Keyword(s):  
Medical Image ◽  
Research Work ◽  
Health Sector ◽  
Image Data ◽  
Medical Data ◽  
Information Network ◽  
Design And Implementation ◽  
Simulation Results ◽  
Medical Image Data ◽  
Secure Transmission

Ideally, secure transmission of medical image data is one of the major challenges in health sector. The National Health Information Network has to protect the data in confidential manner. Storage is also one of the basic concern along with secure transmission. In this paper we propose an algorithm that supports confidentiality, authentication and integrity implementation of the scrambled data before transmitting on the communication medium. Before communication the data is compressed while keeping data encrypted. The research work demonstrate with simulation results. The results shows that the proposed work effectively maintains confidentiality, authentication and integrity. The experimental results evaluated medical image quality like PSNR, MSE, SC, and NAEetc.

scholarly journals Performance Benchmarking of Key-Value Store NoSQL Databases

2018 ◽  
Vol 8 (6) ◽  
pp. 5333
Author(s):  
Omoruyi Osemwegie ◽  
Kennedy Okokpujie ◽  
Nsikan Nkordeh ◽  
Charles Ndujiuba ◽  
Samuel John ◽  
...  
Keyword(s):  
Data Storage ◽  
Web Applications ◽  
Query Language ◽  
Research Work ◽  
Database Systems ◽  
Nosql Databases ◽  
Performance Benchmarking ◽  
Nosql Database ◽  
Structured Query Language ◽  
Web Developers

<p>Increasing requirements for scalability and elasticity of data storage for web applications has made Not Structured Query Language NoSQL databases more invaluable to web developers. One of such NoSQL Database solutions is Redis. A budding alternative to Redis database is the SSDB database, which is also a key-value store but is disk-based. The aim of this research work is to benchmark both databases (Redis and SSDB) using the Yahoo Cloud Serving Benchmark (YCSB). YCSB is a platform that has been used to compare and benchmark similar NoSQL database systems. Both databases were given variable workloads to identify the throughput of all given operations. The results obtained shows that SSDB gives a better throughput for majority of operations to Redis’s performance.</p>

scholarly journals Dynamic Resource Allocation and Memory Management using Deep Convolutional Neural Network

2019 ◽  
Vol 9 (2) ◽  
pp. 608-612
Keyword(s):  
Neural Network ◽  
Resource Allocation ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Data Storage ◽  
Memory Management ◽  
Research Work ◽  
Dynamic Resource Allocation ◽  
Mobile Platform ◽  
Dynamic Resource

Memory management is very essential task for large-scale storage systems; in mobile platform generate storage errors due to insufficient memory as well as additional task overhead. Many existing systems have illustrated different solution for such issues, like load balancing and load rebalancing. Different unusable applications which are already installed in mobile platform user never access frequently but it allocates some memory space on hard device storage. In the proposed research work we describe dynamic resource allocation for mobile platforms using deep learning approach. In Real world mobile systems users may install different kind of applications which required ad-hoc basis. Such applications may be affect to execution performance of system as well space complexity, sometime they also affect another runnable applications performance. To eliminate of such issues, we carried out an approach to allocate runtime resources for data storage for mobile platform. When system connected with cloud data server it store complete file system on remote Virtual Machine (VM) and whenever a single application required which immediately install beginning as remote server to local device. For developed of proposed system we implemented deep learning base Convolutional Neural Network (CNN), algorithm has used with tensorflow environment which reduces the time complexity for data storage as well as extraction respectively.

A Comprehensive Survey on Techniques Based on TPM for Ensuring the Confidentiality in Cloud Data Centers

2019 ◽  
pp. 446-458
Author(s):  
Arun Fera M. ◽  
M. Saravanapriya ◽  
J. John Shiny
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Research Work ◽  
Computing Systems ◽  
Trusted Platform Module ◽  
Cloud Data ◽  
Secure Storage ◽  
Comprehensive Survey ◽  
Cloud Data Centers ◽  
Trusted Platform

Cloud computing is one of the most vital technology which becomes part and parcel of corporate life. It is considered to be one of the most emerging technology which serves for various applications. Generally these Cloud computing systems provide a various data storage services which highly reduces the complexity of users. we mainly focus on addressing in providing confidentiality to users' data. We are proposing one mechanism for addressing this issue. Since software level security has vulnerabilities in addressing the solution to our problem we are dealing with providing hardware level of security. We are focusing on Trusted Platform Module (TPM) which is a chip in computer that is used for secure storage that is mainly used to deal with authentication problem. TPM which when used provides a trustworthy environment to the users. A detailed survey on various existing TPM related security and its implementations is carried out in our research work.

scholarly journals SnowCloudMetrics: Snow Information for Everyone

2020 ◽  
Vol 12 (20) ◽  
pp. 3341
Author(s):  
Ryan L. Crumley ◽  
Ross T. Palomaki ◽  
Anne W. Nolin ◽  
Eric A. Sproles ◽  
Eugene J. Mar
Keyword(s):  
Snow Cover ◽  
Data Storage ◽  
Image Data ◽  
Global Scale ◽  
Google Earth ◽  
Mountain Environments ◽  
Resource Managers ◽  
Moderate Resolution ◽  
Snow Telemetry ◽  
Moderate Resolution Imaging Spectroradiometer

Snow is a critical component of the climate system, provides fresh water for millions of people globally, and affects forest and wildlife ecology. Snowy regions are typically data sparse, especially in mountain environments. Remotely-sensed snow cover data are available globally but are challenging to convert into accessible, actionable information. SnowCloudMetrics is a web portal for on-demand production and delivery of snow information including snow cover frequency (SCF) and snow disappearance date (SDD) using Google Earth Engine (GEE). SCF and SDD are computed using the Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Binary 500 m (MOD10A1) product. The SCF and SDD metrics are assessed using 18 years of Snow Telemetry records at more than 750 stations across the Western U.S. SnowCloudMetrics provides users with the capacity to quickly and efficiently generate local-to-global scale snow information. It requires no user-side data storage or computing capacity, and needs little in the way of remote sensing expertise. SnowCloudMetrics allows users to subset by year, watershed, elevation range, political boundary, or user-defined region. Users can explore the snow information via a GEE map interface and, if desired, download scripts for access to tabular and image data in non-proprietary formats for additional analyses. We present global and hemispheric scale examples of SCF and SDD. We also provide a watershed example in the transboundary, snow-dominated Amu Darya Basin. Our approach represents a new, user-driven paradigm for access to snow information. SnowCloudMetrics benefits snow scientists, water resource managers, climate scientists, and snow related industries providing SCF and SDD information tailored to their needs, especially in data sparse regions.

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