Automated Traffic sign board classification system is one of the key technologies of Intelligent
Transportation Systems (ITS). Traffic Surveillance System is being more and important with improving
urban scale and increasing number of vehicles. This Paper presents an intelligent sign board
classification method based on blob analysis in traffic surveillance. Processing is done by three main
steps: moving object segmentation, blob analysis, and classifying. A Sign board is modelled as a
rectangular patch and classified via blob analysis. By processing the blob of sign boards, the meaningful
features are extracted. Tracking moving targets is achieved by comparing the extracted features with
training data. After classifying the sign boards the system will intimate to user in the form of alarms,
sound waves. The experimental results show that the proposed system can provide real-time and useful
information for traffic surveillance.
Smart home security using Telegram chatbotSanjay Crúzé
A smart security which combines motion detection and face recognition to accurately pin point and detect intruders in user's home and sends alert images, footages as per commands through a telegram chatbot.
Automated Traffic sign board classification system is one of the key technologies of Intelligent
Transportation Systems (ITS). Traffic Surveillance System is being more and important with improving
urban scale and increasing number of vehicles. This Paper presents an intelligent sign board
classification method based on blob analysis in traffic surveillance. Processing is done by three main
steps: moving object segmentation, blob analysis, and classifying. A Sign board is modelled as a
rectangular patch and classified via blob analysis. By processing the blob of sign boards, the meaningful
features are extracted. Tracking moving targets is achieved by comparing the extracted features with
training data. After classifying the sign boards the system will intimate to user in the form of alarms,
sound waves. The experimental results show that the proposed system can provide real-time and useful
information for traffic surveillance.
Smart home security using Telegram chatbotSanjay Crúzé
A smart security which combines motion detection and face recognition to accurately pin point and detect intruders in user's home and sends alert images, footages as per commands through a telegram chatbot.
The Basic Idea Behind “Smart Web Cam Motion Detection Surveillance System” Is To Stop The Intruder To Getting Into The Place Where A High End Security Is Required. This Paper Proposes A Method For Detecting The Motion Of A Particular Object Being Observed. The Motion Tracking Surveillance Has Gained A Lot Of Interests Over Past Few Years. This System Is Brought Into Effect Providing Relief To The Normal Video Surveillance System Which Offers Time-Consuming Reviewing Process. Through The Study And Evaluation Of Products, We Propose A Motion Tracking Surveillance System Consisting Of Its Method For Motion Detection And Its Own Graphic User Interface.
(Slides) UbiREMOTE: Framework for Remotely Controlling Networked Appliances t...Naoki Shibata
Kiyokawa, K., Yamamoto, S., Shibata, N., Yasumoto, K., Ito, M.: UbiREMOTE: Framework for Remotely Controlling Networked Appliances through Interaction with 3D Virtual Space, Proc. of ACM Multimedia Systems 2010 (MMSys2010), pp.271-280, DOI:10.1145/1730836.1730870 (Feb. 2010).
http://ito-lab.naist.jp/mediawiki/images/6/60/100223mmsys.pdf
In this paper, we propose a framework named “UbiREMOTE”for controlling information appliances connected to a home network with a unified and intuitive user interface from a remote place. The UbiREMOTE framework provides users with a way to control appliances in a home through a virtual space drawn on a mobile terminal screen which reflects the latest conditions of the real appliances and the rooms in the home. With UbiREMOTE, a user controls appliances by (1) moving to the front of an appliance, (2) choosing the appliance to control and (3) pushing buttons on the virtual remote controller which imitates the real remote controller for the appliance or the real console. In this paper, we propose a method to improve the drawing speed of 3D virtual space on mobile terminals and a method for automatically reflecting condition changes of the real space in the virtual space. We implemented the methods and evaluated the performance. The results showed that the proposed methods can be practically used on small mobile terminals.
Automatic Real Time Auditorium Power Supply Control using Image Processingidescitation
One of the major problems in the most populated and developing countries like
India, is Energy or Power crisis. Hence, there is a pressing need to conserve power. There
are many simple ways to save electricity, like using the electric and electronic gadgets
whenever and wherever needed and switching them off, while not in use. But in places such
as large auditoriums and meeting halls, there will be a fan or an Air-conditioner keeps
running in unmanned area too, even before the people arrive. This contributes to a
considerable amount of electricity wastage. There are many ways to prevent this wastage,
like, installing IR sensors to detect people etc. These methods are quite costlier and complex
for larger areas. Hence, here we propose a new method of controlling the power supply of
auditoriums using, Image Processing. Here first we take a reference image of an empty
auditorium and any change in that reference image is detected and then according to that
change respective equipments alone are turned on. Thus power wastage is controlled. This is
dual usage system in which a camera is used for detecting people as well as surveillance
purposes. This is very simple, efficient and cheaper technique to save energy. Another big
advantage is, we can extend this up to applications like home automation etc.
Analysis of Inertial Sensor Data Using Trajectory Recognition Algorithmijcisjournal
This paper describes a digital pen based on IMU sensor for gesture and handwritten digit gesture
trajectory recognition applications. This project allows human and Pc interaction. Handwriting
Recognition is mainly used for applications in the field of security and authentication. By using embedded
pen the user can make hand gesture or write a digit and also an alphabetical character. The embedded pen
contains an inertial sensor, microcontroller and a module having Zigbee wireless transmitter for creating
handwriting and trajectories using gestures. The propound trajectory recognition algorithm constitute the
sensing signal attainment, pre-processing techniques, feature origination, feature extraction, classification
technique. The user hand motion is measured using the sensor and the sensing information is wirelessly
imparted to PC for recognition. In this process initially excerpt the time domain and frequency domain
features from pre-processed signal, later it performs linear discriminant analysis in order to represent
features with reduced dimension. The dimensionally reduced features are processed with two classifiers –
State Vector Machine (SVM) and k-Nearest Neighbour (kNN). Through this algorithm with SVM classifier
provides recognition rate is 98.5% and with kNN classifier recognition rate is 95.5% .
vSmart - an integrated system for the smart control of domestic appliances in local environments based on monitored user presence and activity; thereby achieving multidimensional user-convenience and using modern technology to endow a sustainable environment in our everyday lives.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A NOVEL BACKGROUND SUBTRACTION ALGORITHM FOR PERSON TRACKING BASED ON K-NN csandit
Object tracking can be defined as the process of detecting an object of interest from a video scene and keeping track of its motion, orientation, occlusion etc. in order to extract useful
information. It is indeed a challenging problem and it’s an important task. Many researchers are getting attracted in the field of computer vision, specifically the field of object tracking in video surveillance. The main purpose of this paper is to give to the reader information of the present state of the art object tracking, together with presenting steps involved in Background Subtraction and their techniques. In related literature we found three main methods of object tracking: the first method is the optical flow; the second is related to the background subtraction, which is divided into two types presented in this paper, and the last one is temporal
differencing. We present a novel approach to background subtraction that compare a current frame with the background model that we have set before, so we can classified each pixel of the image as a foreground or a background element, then comes the tracking step to present our object of interest, which is a person, by his centroid. The tracking step is divided into two different methods, the surface method and the K-NN method, both are explained in the paper.Our proposed method is implemented and evaluated using CAVIAR database.
A Digital Pen with a Trajectory Recognition AlgorithmIOSR Journals
Abstract : Now a days, the development of miniaturization technologies in electronic circuits and components has seriously decreased the dimension and weight of consumer electronic products, those are smart phones and handheld computers, and thus prepared them more handy and convenient. This paper contains an accelerometer-based digital pen for handwritten digit and gesture trajectory recognition applications. The digital pen consists of a triaxial accelerometer, a microcontroller, and an Zigbee wireless transmission module for sensing and collecting accelerations of handwriting and gesture trajectories. with this project we can do human computer interaction. Users can utilize this pen to write digits or make hand gestures, and the accelerations of hand motions calculated by the accelerometer are wirelessly transmitted to a computer for online trajectory recognition. So, by varying the position of mems (micro electro mechanical systems) we can capable to show the alphabetical characters in the PC. The acceleration signals calculated from the triaxial accelerometer are transmitted to a computer via the wireless module. Keywords - ARM, Zigbee, Sensors module
Computer m
emory is expensive and the recording of data captured by a webcam needs memory. I
n order to minimize the
memory usage in recording data from human motion as recorded from the webcam, this algorithm will use motion
detection as applied to a process to measure the change in speed or vector of an object in the field of view. This
applicat
ion only works if there is a motion detected and it will automatically save the captured image in its designated
folder.
The Basic Idea Behind “Smart Web Cam Motion Detection Surveillance System” Is To Stop The Intruder To Getting Into The Place Where A High End Security Is Required. This Paper Proposes A Method For Detecting The Motion Of A Particular Object Being Observed. The Motion Tracking Surveillance Has Gained A Lot Of Interests Over Past Few Years. This System Is Brought Into Effect Providing Relief To The Normal Video Surveillance System Which Offers Time-Consuming Reviewing Process. Through The Study And Evaluation Of Products, We Propose A Motion Tracking Surveillance System Consisting Of Its Method For Motion Detection And Its Own Graphic User Interface.
(Slides) UbiREMOTE: Framework for Remotely Controlling Networked Appliances t...Naoki Shibata
Kiyokawa, K., Yamamoto, S., Shibata, N., Yasumoto, K., Ito, M.: UbiREMOTE: Framework for Remotely Controlling Networked Appliances through Interaction with 3D Virtual Space, Proc. of ACM Multimedia Systems 2010 (MMSys2010), pp.271-280, DOI:10.1145/1730836.1730870 (Feb. 2010).
http://ito-lab.naist.jp/mediawiki/images/6/60/100223mmsys.pdf
In this paper, we propose a framework named “UbiREMOTE”for controlling information appliances connected to a home network with a unified and intuitive user interface from a remote place. The UbiREMOTE framework provides users with a way to control appliances in a home through a virtual space drawn on a mobile terminal screen which reflects the latest conditions of the real appliances and the rooms in the home. With UbiREMOTE, a user controls appliances by (1) moving to the front of an appliance, (2) choosing the appliance to control and (3) pushing buttons on the virtual remote controller which imitates the real remote controller for the appliance or the real console. In this paper, we propose a method to improve the drawing speed of 3D virtual space on mobile terminals and a method for automatically reflecting condition changes of the real space in the virtual space. We implemented the methods and evaluated the performance. The results showed that the proposed methods can be practically used on small mobile terminals.
Automatic Real Time Auditorium Power Supply Control using Image Processingidescitation
One of the major problems in the most populated and developing countries like
India, is Energy or Power crisis. Hence, there is a pressing need to conserve power. There
are many simple ways to save electricity, like using the electric and electronic gadgets
whenever and wherever needed and switching them off, while not in use. But in places such
as large auditoriums and meeting halls, there will be a fan or an Air-conditioner keeps
running in unmanned area too, even before the people arrive. This contributes to a
considerable amount of electricity wastage. There are many ways to prevent this wastage,
like, installing IR sensors to detect people etc. These methods are quite costlier and complex
for larger areas. Hence, here we propose a new method of controlling the power supply of
auditoriums using, Image Processing. Here first we take a reference image of an empty
auditorium and any change in that reference image is detected and then according to that
change respective equipments alone are turned on. Thus power wastage is controlled. This is
dual usage system in which a camera is used for detecting people as well as surveillance
purposes. This is very simple, efficient and cheaper technique to save energy. Another big
advantage is, we can extend this up to applications like home automation etc.
Analysis of Inertial Sensor Data Using Trajectory Recognition Algorithmijcisjournal
This paper describes a digital pen based on IMU sensor for gesture and handwritten digit gesture
trajectory recognition applications. This project allows human and Pc interaction. Handwriting
Recognition is mainly used for applications in the field of security and authentication. By using embedded
pen the user can make hand gesture or write a digit and also an alphabetical character. The embedded pen
contains an inertial sensor, microcontroller and a module having Zigbee wireless transmitter for creating
handwriting and trajectories using gestures. The propound trajectory recognition algorithm constitute the
sensing signal attainment, pre-processing techniques, feature origination, feature extraction, classification
technique. The user hand motion is measured using the sensor and the sensing information is wirelessly
imparted to PC for recognition. In this process initially excerpt the time domain and frequency domain
features from pre-processed signal, later it performs linear discriminant analysis in order to represent
features with reduced dimension. The dimensionally reduced features are processed with two classifiers –
State Vector Machine (SVM) and k-Nearest Neighbour (kNN). Through this algorithm with SVM classifier
provides recognition rate is 98.5% and with kNN classifier recognition rate is 95.5% .
vSmart - an integrated system for the smart control of domestic appliances in local environments based on monitored user presence and activity; thereby achieving multidimensional user-convenience and using modern technology to endow a sustainable environment in our everyday lives.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A NOVEL BACKGROUND SUBTRACTION ALGORITHM FOR PERSON TRACKING BASED ON K-NN csandit
Object tracking can be defined as the process of detecting an object of interest from a video scene and keeping track of its motion, orientation, occlusion etc. in order to extract useful
information. It is indeed a challenging problem and it’s an important task. Many researchers are getting attracted in the field of computer vision, specifically the field of object tracking in video surveillance. The main purpose of this paper is to give to the reader information of the present state of the art object tracking, together with presenting steps involved in Background Subtraction and their techniques. In related literature we found three main methods of object tracking: the first method is the optical flow; the second is related to the background subtraction, which is divided into two types presented in this paper, and the last one is temporal
differencing. We present a novel approach to background subtraction that compare a current frame with the background model that we have set before, so we can classified each pixel of the image as a foreground or a background element, then comes the tracking step to present our object of interest, which is a person, by his centroid. The tracking step is divided into two different methods, the surface method and the K-NN method, both are explained in the paper.Our proposed method is implemented and evaluated using CAVIAR database.
A Digital Pen with a Trajectory Recognition AlgorithmIOSR Journals
Abstract : Now a days, the development of miniaturization technologies in electronic circuits and components has seriously decreased the dimension and weight of consumer electronic products, those are smart phones and handheld computers, and thus prepared them more handy and convenient. This paper contains an accelerometer-based digital pen for handwritten digit and gesture trajectory recognition applications. The digital pen consists of a triaxial accelerometer, a microcontroller, and an Zigbee wireless transmission module for sensing and collecting accelerations of handwriting and gesture trajectories. with this project we can do human computer interaction. Users can utilize this pen to write digits or make hand gestures, and the accelerations of hand motions calculated by the accelerometer are wirelessly transmitted to a computer for online trajectory recognition. So, by varying the position of mems (micro electro mechanical systems) we can capable to show the alphabetical characters in the PC. The acceleration signals calculated from the triaxial accelerometer are transmitted to a computer via the wireless module. Keywords - ARM, Zigbee, Sensors module
Computer m
emory is expensive and the recording of data captured by a webcam needs memory. I
n order to minimize the
memory usage in recording data from human motion as recorded from the webcam, this algorithm will use motion
detection as applied to a process to measure the change in speed or vector of an object in the field of view. This
applicat
ion only works if there is a motion detected and it will automatically save the captured image in its designated
folder.
Surveillance using the video is a bit sophisticated task, yet making use of
technology things can be done perfect. Security has been so difficult in the past that it was
overlooked or avoided by security installers unless absolutely necessary. The present focus
of computer vision Technology aimed at automating the analysis of Closed Circuit Tele
Vision (CCTV) footages. This includes automatic identification of objects in a raw video,
following those objects over time and between cameras, and the interpretation of those
object’s appearance and movements. Here achieving video analytics by implementing its
segments, through Open CV with an e.g., Extracting the edges of a live video through web
cam and finding the motion detection in Live video. In this paper we even discuss about the
feature of 3-D sensors in video surveillance.
This paper represents a survey of various methods of video surveillance system which improves the security. The aim of this paper is to review of various moving object detection technics. This paper focuses on detection of moving objects in video surveillance system. Moving body detection is first important task for any video surveillance system. Detection of moving object is a challenging task. Tracking is required in higher level applications that require the location and shape of object in every frame. In this survey,paper described about optical flow method, Background subtraction, frame differencing to detect moving object. It also described tracking method based on Morphology technique.
Keywords -- Frame separation, Pre-processing, Object detection using frame difference, Optical flow,
Temporal Differencing and background subtraction. Object tracking
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Abnormal activity detection in surveillance video scenesTELKOMNIKA JOURNAL
Automated detection of abnormal activity assumes a significant task in surveillance applications. This paper presents an intelligent framework video surveillance to detect abnormal human activity in an academic environment that takes into account the security and emergency aspects by focusing on three abnormal activities (falling, boxing and waving). This framework designed to consist of the two essential processes: the first one is a tracking system that can follow targets with identify sets of features to understand human activity and measure descriptive information of each target. The second one is a decision system that can realize if the activity of the target track is "normal" or "abnormal” then energizing alarm when recognized abnormal activities.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
H028038042
1. Research Inventy: International Journal Of Engineering And Science
Vol.2, Issue 8 (March 2013), Pp 38-42
Issn(e): 2278-4721, Issn(p):2319-6483, Www.Researchinventy.Com
38
Webcam Based Intelligent Surveillance System
1
Akshada Deshmukh, 2
Harshalata Wadaskar, 3
Leena Zade,
4
Neha Dhakate, 5
Preetee Karmore.
1,2,3,4,
(Student, Dept.of Computer Science and Engineering, Dr. Babasaheb Ambedkar College of Engineering
,Nagpur, Maharashtra-441110, India)
5
(HOD, Dept.of Computer Science and Engineering, Dr. Babasaheb Ambedkar College of Engineering
,Nagpur, Maharashtra-441110, India)
Abstract -. An intelligent monitoring sensor is an application which is developed from the security point of
view. The objective of this project is to develop a system that monitors the area in which it is being implemented.
An Intelligent Monitoring Sensor is applicable in the area where no one is permissible to enter, also where we
need to detect if any motion has been done. For this a digital camera is used. By combining the software and
camera we can use this system as an Intelligent Monitoring Sensor.The Camera is used to catch the live images
of the area in which it is being implemented, if any object is moving. The captured images are stored in a
particular folder. The stored images will be then useful to work on. As the software detects the motion, it sends
the signal from a transmitter, which is connected to the PC. The transmitter will send the wireless signal to the
receiver out somewhere else, in the form of radio frequency. In this way the system will provide the security
against any misdeed.
Keywords – image capturing, motion detection, monitoring, receiver, security, transmitter.
I. INTRODUCTION
Intelligent Monitoring Sensor is an application in which a digital camera is used as a powerful motion
detector. Instead of using various ultra-sonic or other sensors, we are using camera as the sensor here. By
combining the software and the camera we can use this system as a Intelligent monitoring Sensor.
An Intelligent Monitoring Sensor can be used for security in restricted areas, where no one is allowed to
visit or enter the space during particular time. For this a digital camera is used. By combining the software and
camera we can use this system as an Intelligent Monitoring Sensor.If any changes has been found the camera
capture the images at the rate of one image per 60msec and stores them in the folder. The stored images will be
then useful to work on. As the changes have been detected, the transmitter which is connected to the PC sends the
wireless signal to the receiver at the other end.
There are three security levels in the software to control the monitoring.
[1] High: This level will focus on the particular object only and can sense within the range of 1meter only
[2] Middle: In this level the security will be less as compared to High Level .here it will sense the human as
well as object.
[3] Low: It’s the lowest level security. This mode is basically used for monitoring only.
The main modules of the project are:
[1] Login Form designing
[2] Camera Interfacing
[3] Image Capturing & Storage
[4] Hardware Interfacing
[5] Motion Detection
1.1. First Module :- Login Form designing.
The Login form is designed to provide authentication. If the login is successfully done, then it will
switch to next form i.e. Option Form, where we have three options-
2. Webcam Based Intelligent Surveillance…
39
[1] Motion Detection Form
[2] Image List Form
[3] Exit
In Motion Detection Form, the motion caused ,if any, is analyzed and thus the indications are given to the
authenticated person. In the second option, all the images can be viewed wherein we can see what all changes
have been done and by whom. Whereas, the third option is the way to exit an application.
1.2. Second Module :- Camera Interfacing.
This form contains the list box where the list of all the camera devices connected to the software are
displayed . By default the first camera is selected, but we can select any of the available devices from the
listbox .After the device is selected, the camera is interfaced through coding part. Then there is a button
‘Activate Motion Detection’, through which we can select the mode of our working and the application is set
on. Here we actually have three modes -
High
Middle
Low
1.3. Third Module :- Image Capturing & storage.
Whenever any changes between the two corresponding images have been detected, the application
starts capturing the images and they are stored into the folder using AVICAP32.dll class. At the same time , a
wireless signal is transmitted to the receiver through .Wave file.
AVICap routes video and audio stream data from a captured window to a file named CAPTURE.AVI in
the root directory of the current drive. AVICap window class provides applications with a message-based
interface to access video and waveform-audio acquisition hardware and to control the process of streaming
video capture to disk. AVICap window is efficient enough to control the process of streaming video capture
to disk.
1.4. Fourth Module :- Motion Detection.
The basic working of motion detection module is comparison between two images. The first image is
the one when we activate the application and the second image is of the second instant of time. When the
application recognizes any changes between two corresponding images, it calls the next module i.e Image
Capturing, and if not, it keeps monitoring again.
1.5. Fifth Module :- Hardware Interfacing
When the software will detect any movement or changes in the image, it will send a signal (hex value)
to LPT port. A transmitter will be connected to the LPT port of the PC. The transmitter will transmit the signal to
the receiver and it will play the buzzer at the receiver’s end. Then the further actions will be taken by user.
II. LITERATURE REVIEW
There are many existing devices in market such as CCTv Cameras, IP camera, Infrared Sensor, Laser
Sensor etc.
CCTv : Implementation of CCTv cameras are very costly and has drawbacks since it require constant
monitoring of every activity which is not as ease. Continuous manual visualization hampers the productivity and
time. Criminals can penetrate into the CCTV system, thereby facilitating criminal acts.
IP camera : Implementation of IP cameras are also very costly and not feasible. This system cause major
problems as it becomes open to hackers via internet(false bomb threats, called in hoaxers while watching the
cameras.) .
Infrared Sensor and Laser Sensor: These devices are quite economic in comparison to above devices however
they have some drawbacks too. These devices are difficult to install and rarely available. One of the major
disadvantages of infrared sensors is the size required to provide good resolution to the the signal.
3. Webcam Based Intelligent Surveillance…
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III. INDENTATIONS AND EQUATIONS
3.1 Moving-Object Detection
The detection of moving objects is the first stage of a typical surveillance system. Motion detection
aims at segmenting the regions pertaining to moving objects from the rest of the image. Subsequent processes
such as tracking and behavior analysis are greatly dependent on the performance of this stage. Many algorithms
have been suggested to solve the problem of motion detection, where the moving pixels are identified by
thresholding the temporal difference between the frames; background subtraction where detection occurs by
comparing the incoming frame with a background model of the scene that is built by modeling the pixel
intensity either by a single Gaussian distribution , a mixture of Gaussians , or using the maximum, minimum and
maximum intensity difference as in ; and optical flow approaches that use characteristics of flow vectors of
moving objects over time to detect moving regions in image sequences.
3.2 Temporal Variance Based Motion Detection:
In our system, we use the temporal variance as a parameter to detect moving areas in a stationary
scenes. The mean and variance of the intensity value at each pixel is calculated over a window of several
previous frames and updated recursively for every new frame. This value of the variance is used directly
afterward for the detection of moving area. The use of temporal variance for motion detection has some nice
properties:
[1] The variance of intensity at a certain pixel depends on both the amplitude of changes and the duration of
this
change so it is more robust to transient noises incurred by moving texture.
[2] There is no need for background training period as this method can build the model with the existence of
moving objects on the scene.
The mean and variance for the intensity at each pixel (i, j) are recursively updated using a simple
exponentially decaying adaptive filter as follows:
m(i, j, t) = αm(i, j, t − 1) + (1 − α)x(i, j, t)
m2(i, j, t) = αm2(i, j, t − 1) + (1 − α)x2(i, j, t)
σ2(i, j, t) = m2(i, j, t) − m2(i, j, t) …..(1)
where: x(i, j, t) is the intensity, m(i, j, t) is the first moment, m2(i, j, t) is the second moment and σ2(i, j, t) is the
variance at pixel (i, j) at time t, α is the decay rate, that can be rewritten with respect to the filter window size N
as:
α = (N – 1)/N
N =1/(1 – α) ….(2)
3.3 Background Modeling:
In order to remove the trail effect, a background model is built by recursively updating another set of
mean and variance as follows:
mbg(i, j, t) = αbgmbg(i, j, t − 1) + (1 − αbg)x(i, j, t)
m2bg(i, j, t) = αbgm2bg(i, j, t − 1) + (1 − αbg)x2(i, j, t)
σ2
bg(i, j, t) = m2bg(i, j, t) − m2
bg(i, j, t)
where:
mbg(i, j, t) is the background first moment,
m2bg(i, j, t) is the background second moment, and
σbg(i, j, t)2 is the background variance for the background at pixel (i, j) at time t. αbg is the background model
decay rate that can also be written with respect to the background
filter window size Nbg
The background model is used to obtain a confidence weight representing the confidence of this pixel
being a part of the foreground. This confidence weight is obtained as a function of the distance between the
pixel intensity and the background model
4. Webcam Based Intelligent Surveillance…
41
C(i, j, t) = f _|x(i, j, t) − mbg(i, j, t)|_σbg(i, j, t)
where C(i, j, t) is the confidence weight that the pixel (i, j) is part of the foreground and f is a nonlinear-mapping
function– such as sigmoid– to map the distance to range of [0,1] and to emphasize the large distance points. The
final binary detection map L(i, j, t) is obtained as follows:
L(i, j, t) = _ 1 if C(i, j, t)σ(i, j, t) ≥ Threshold 0 if C(i, j, t)σ(i, j, t) < Threshold
where the value of Threshold can be obtained either empirically or by multiplying the average background
variance by a factor.
IV FIGURES AND TABLES
fig:flowchart
V. TRANSMITTER AND RECEIVER KIT
Fig: Transmitter kit Fig: Receiver kit
WORKING OF TRANSMITTER KIT:
[1] When the power is supplied to the circuit, the frequency is generated
[2] This frequency is traveled through gang condenser where it is tuned to 3.587MHz
[3] Then the frequency is converted into voltage. This voltage is amplified using the transistor T1
[4] During this process the noise is generated which is filtered using capacitive-resistive filter
[5] Now this voltage is travelled through capacitor c3 where the capacitor gets charged
[6] To transmit the signal this voltage is again converted into frequency using induction coil and thus it
generates emf.
[7] Due to this induced emf, the frequency is generated, which is then transmitted by antenna and gives
wireless signal at the receiver end.
5. Webcam Based Intelligent Surveillance…
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WORKING OF RECEIVER KIT:
[1] Antena receives signal through transmitter, the capacitor c3 gets charged and it converts frequency to
volatge at 9volt and the noise is generated.
[2] Then the current is forwarded through the transformer through the inductively coupled conductors in the
transformer.
[3] Then the capacitive-resistive coil filters the noise generated in the received signal.
[4] The silicon diode is one way conductor and provides no backing of voltage and amplifies the signal.
[5] Inductor converts voltage to frequency.
[6] Also there is a filtering circuit which filters 2-3 times to drop the weak signals.
[7] Further the NPN transistor amplifies the current which acts as a switch.
[8] The capacitor c6,c9 and c10 gets charged which holds the energy for a while and notification is given to
the receiver through buzzer.
VI. CONCLUSION
Webcam Surveillance Standard is advanced video surveillance software. Users can effortlessly monitor
home, office, cradle, parking area, storehouse, UFO or any other premises 24-hours a day. Timestamped image
capturing let users capture details of events precisely when they happen. Simply connect a USB or FireWire
Camera to your PC. Different environments have different surveillance requirements. A large facility like a
parking lot, store, residence, or hall cannot be monitored efficiently by a single camera. Advances in PC based
surveillance software now allow anyone with a webcam to setup a robust, effective and inexpensive surveillance
system. Today, all you need for securing your assets is a PC, a couple of webcams and software like
Webcam Based Intelligent Surveillance System.
Traditionally, CCTV (Closed Circuit TV) based Surveillance Systems were used for multi camera
monitoring. This solution was expensive due to the huge hardware costs.
Applications :
[1] Office Security
[2] Army Surveillance
[3] Museum
[4] Bank Security
[5] Space Research
[6] Home Security
REFERENCES
[1] Bramberger, Pflugfelder, Maier, Rinner, Strobl, Schwabach, A Smart Camera for Traffic Surveillance (2000)
[2] Trans. on systems, man, and cybernetics part C: Applications and Reviews, Vol.34, NO.3, AUGUST 2004.
[3] Trans. on systems, man, and cybernetics part C: Applications and Reviews, Vol.34, NO.3, AUGUST 2004.
[4] Mohemed F Abdelkader, Integrated Motion Detection & Tracking for Visual Surveillance (ICVS 2006).
[5] Raman Maini & Dr. Himanshu Aggarwal,International Journal of Image Processing (IJIP), Volume (3) :
Issue (1)
[6] An Improved Motion Detection Method for Real-Time Surveillance Nan Lu, Jihong Wang, Q.H. Wu and Li Yang(19 February
2008).
[7] W. Hu,T. Tan,L.Wang, and S. Maybank. A survey on visual surveillance of object motion and behaviors, IEEE
[8] N.R.Mokhtar, Nor Hazlyna Harun,M.Y.Mashor, 2H.Roseline , 1Nazahah Mustafa, R.Adollah ,H. Adilah, N.F.Mohd Nasir,” Image
Enhancement Techniques Using Local,Global, Bright, Dark and Partial Contrast Stretching For Acute Leukemia Images”
Proceedings of the World Congress on Engineering 2009 Vol I WCE 2009.
[9] Implementation of webcam based sytem for surveillance monitoring,Brahmanandha Prabhu R,Arul Prabhar A,Garima
Bohra,Proceeding of ASCNT-2010,CDAC,Noida,India.
[10] G. D. Hager, and P. N. Belhumeur. Efficient region tracking with parametric models of geometry and illumination, IEEE Trans.
PAMI, vol. 20.
[11] W. E. L. Grimson, C. Stauffer, R. Romano, and L. Lee. Using adaptive tracking to classify and monitor activities in a site, in Proc.
IEEE Conf. CVPR, Santa Barbara, CA.
Books:
[1] Book: Mastering Visual Basic 6.0 by Evangelos Petroutsos
[2] Book: Visual Basic Bible by Douglas Herger