A tutorial about the API for the description of a monitoring infrastructure currently discussed inside the OCCI working group.
The slides start by giving the basic concepts, proceed with a description of the entities that implement the monitoring infrastructure, and conclude with a step by step definition of a non-trivial monitoring infrastructure.
Automated deployment of a microservice based monitoring architectureAugusto Ciuffoletti
The document discusses two topics: microservices and cloud monitoring. Microservices involve breaking applications into small, independent components. Cloud monitoring allows users to monitor cloud resources. The author proposes an "on demand monitoring" approach using a microservices-based infrastructure that provides scalable and configurable monitoring as a service. It automatically deploys a monitoring system that can be tailored to the user's needs and scales from simple to complex setups.
Monitoring a virtual network infrastructure - An IaaS perspectiveAugusto Ciuffoletti
The document discusses the challenges of providing network resources as part of an Infrastructure as a Service (IaaS) cloud computing model. While IaaS has traditionally focused on storage and computing resources, the networking capabilities now exist to provision virtual network infrastructure as well. However, IaaS providers still typically only offer flat local area networks rather than composite network topologies that some users require. The key technology that enables virtual private networks is virtual bridging using VLAN tagging, which allows flexible virtual network configurations. For network monitoring in IaaS, a proxy that interacts with users is proposed to dynamically configure monitoring while maintaining provider control over network devices.
The document discusses the Open Cloud Computing Interface (OCCI), which aims to provide an open standard interface for cloud computing. It describes OCCI's goals of allowing interoperability between different cloud providers and preventing vendor lock-in. The core OCCI model defines basic resource and link entity types and supports extensions for additional types and functionality. OCCI uses a RESTful API and represents entities with URIs to allow their creation, retrieval, updating and deletion. Implementations of OCCI have been made for various programming languages and cloud platforms.
The document discusses extending the OCCI API with monitoring capabilities. It proposes adding two new types: Collector and Sensor. The Collector would be a link that extracts operational parameters from a source resource and delivers them to a target resource. The Sensor would be a resource that processes or aggregates output from one or more Collectors, such as by filtering, interpolating, or combining monitoring data. Plugins would provide different options for parameters, transport methods, and ways to aggregate and process data.
The document describes an OCCI extension for monitoring cloud resources from both an administrator and user perspective. It proposes representing monitoring entities like sensors and collectors as OCCI resource and link types. Sensors would aggregate and deliver measurements, while collectors produce measurements. These would be further described through mixins that detail their specific monitoring functionality. The proposal aims to provide on-demand, scalable monitoring as a service to users through a standardized and customizable OCCI interface.
Automated deployment of a microservice based monitoring architectureAugusto Ciuffoletti
The document discusses two topics: microservices and cloud monitoring. Microservices involve breaking applications into small, independent components. Cloud monitoring allows users to monitor cloud resources. The author proposes an "on demand monitoring" approach using a microservices-based infrastructure that provides scalable and configurable monitoring as a service. It automatically deploys a monitoring system that can be tailored to the user's needs and scales from simple to complex setups.
Monitoring a virtual network infrastructure - An IaaS perspectiveAugusto Ciuffoletti
The document discusses the challenges of providing network resources as part of an Infrastructure as a Service (IaaS) cloud computing model. While IaaS has traditionally focused on storage and computing resources, the networking capabilities now exist to provision virtual network infrastructure as well. However, IaaS providers still typically only offer flat local area networks rather than composite network topologies that some users require. The key technology that enables virtual private networks is virtual bridging using VLAN tagging, which allows flexible virtual network configurations. For network monitoring in IaaS, a proxy that interacts with users is proposed to dynamically configure monitoring while maintaining provider control over network devices.
The document discusses the Open Cloud Computing Interface (OCCI), which aims to provide an open standard interface for cloud computing. It describes OCCI's goals of allowing interoperability between different cloud providers and preventing vendor lock-in. The core OCCI model defines basic resource and link entity types and supports extensions for additional types and functionality. OCCI uses a RESTful API and represents entities with URIs to allow their creation, retrieval, updating and deletion. Implementations of OCCI have been made for various programming languages and cloud platforms.
The document discusses extending the OCCI API with monitoring capabilities. It proposes adding two new types: Collector and Sensor. The Collector would be a link that extracts operational parameters from a source resource and delivers them to a target resource. The Sensor would be a resource that processes or aggregates output from one or more Collectors, such as by filtering, interpolating, or combining monitoring data. Plugins would provide different options for parameters, transport methods, and ways to aggregate and process data.
The document describes an OCCI extension for monitoring cloud resources from both an administrator and user perspective. It proposes representing monitoring entities like sensors and collectors as OCCI resource and link types. Sensors would aggregate and deliver measurements, while collectors produce measurements. These would be further described through mixins that detail their specific monitoring functionality. The proposal aims to provide on-demand, scalable monitoring as a service to users through a standardized and customizable OCCI interface.
The extension of the OCCI framework to describe a monitoring infrastructure.
A demo explains how the infrastructure is generated starting from the OCCI specification.
The source of the demo (in Java) is available in the repository of the OCCI working group.
The document discusses several projects related to analyzing data from Fitbit activity monitors. It covers developing APIs to access Fitbit data using OAuth protocols and ensuring data accuracy. It also discusses using Fitbit data for predictive analytics to detect potential depression and comparing Fitbit and treadmill step count data. Machine learning algorithms like SVM and Bayes classification are used for the predictive analytics. Linear regression is used to analyze the relationship between Fitbit and treadmill step counts. The projects aim to better utilize Fitbit data through APIs, analytics and comparing against other activity monitors.
Leveraging Python Telemetry, Azure Application Logging, and Performance Testi...Stackify
In today's fast-paced digital landscape, ensuring the reliability, performance, and observability of applications is crucial. This involves leveraging tools and techniques such as Python telemetry, Azure application logging, and performance testing in production. These practices help in monitoring application health, diagnosing issues, and optimizing performance, ultimately leading to a better user experience and more robust applications. In this PDF, we'll explore these concepts in detail and understand how they can be effectively implemented.
The document describes ObserveIT software that records and replays terminal, Citrix, and console user sessions. It provides key details about the company, product capabilities, customer base, benefits, and technical architecture. Specifically, it allows compliance auditing by tracking all access, remote vendor monitoring, and root cause analysis through playback of exact user actions. The software has a global presence and is deployed across industries for security, compliance, troubleshooting, and SLA validation.
CyberLab Training Division :
Intel VTune Amplifier is a commercial application for software performance analysis for 32 and 64-bit x86 based machines, and has both GUI and command line interfaces. It is available for both Linux and Microsoft Windows operating systems. Although basic features work on both Intel and AMD hardware, advanced hardware-based sampling requires an Intel-manufactured CPU.
Whether you are tuning for the first time or doing advanced performance optimization, Intel® VTune Amplifier provides a rich set of performance insight into CPU & GPU performance, threading performance & scalability, bandwidth, caching and much more. Analysis is faster and easier because VTune Amplifier understands common threading models and presents information at a higher level that is easier to interpret. Use its powerful analysis to sort, filter and visualize results on the timeline and on your source.
It is available as part of Intel Parallel Studio or as a stand-alone product.
VTune Amplifier assists in various kinds of code profiling including stack sampling, thread profiling and hardware event sampling. The profiler result consists of details such as time spent in each sub routine which can be drilled down to the instruction level. The time taken by the instructions are indicative of any stalls in the pipeline during instruction execution. The tool can be also used to analyze thread performance. The new GUI can filter data based on a selection in the timeline.
For More Details.
Visit: http://www.cyberlabzone.com
Creating aggregated Sensu monitors, or how to monitor a group of monitorsMaggie Moreno
This document describes how to create aggregated Sensu monitors by querying logs stored in Elasticsearch. It discusses sending Sensu check logs and outputs to Elasticsearch (steps 1-2), creating a Sensu check called Senseuss that defines an Elasticsearch query and expressions to alert on query results (step 3), and provides examples of using Senseuss.
After a model has been deployed, it's important to understand how the model is being used in production, and to detect any degradation in its effectiveness due to data drift. This module describes tech- niques for monitoring models and their data.
IRJET- Full Body Motion Detection and Surveillance System ApplicationIRJET Journal
1) The document discusses a system for real-time full-body motion detection and surveillance using computer vision techniques.
2) It involves comparing video frames over time to detect motion by treating videos as stacks of frames and looking for differences between frames.
3) The goal is to track body motion in real time using OpenCV for applications like surveillance systems, pose estimation, and other filters.
COIT20270 Application Development for Mobile PlatformsWeek 4.docxmary772
COIT20270 Application Development for Mobile Platforms
Week 4: Designing UI’s with Views
Dr. R. Balsys, CQU, 2012.
Source: Beginning Android Programming with Android Studio, J.F. DiMarzio, 2016
Week 4 – Designing UI’s with Views
Objectives, to understand how to use:
basic views
TextView views
Button, ImageButton, EditText, Checkbox, ToggleButton, RadioButton and RadioGroup views
ProgressBar views
AutoCompleteTextView views
Picker views – TimePicker and DatePicker
CQU - COIT20270 Application Development for Mobile Platforms
Basic Views
Basic views allow you to display text and perform selection. This includes-
TextView
Button
ImageButton
EditText
Checkbox
ToggleButton
RadioButton
RadioGroup
CQU - COIT20270 Application Development for Mobile Platforms
3
TextView view
This basic view allows you to display static text
<TextView> elements are contained in the main.xml file in the res/layout directory
CQU - COIT20270 Application Development for Mobile Platforms
4
Other Basic Views
Other basic views you will use include:
Button – a push button widget
ImageButton – a Button with an image on it
EditText – subclass of TextView with editable text
CheckBox – a button with checked and unchecked states
RadioGroup and RadioButton – RadioGroup is used to group RadioButton’s
ToggleButton – displays states using a light indicator
CQU - COIT20270 Application Development for Mobile Platforms
5
…Other Basic Views
Use “fill_parent” for android:layout_width or android:layout_height so that the basic view fills the parent view space
Use “wrap_content” for android:layout_width or android:layout_height so that the basic view tightly bounds the content only
The android:src value is used to define the image for an ImageButton
You can use the style attribute to set the style of a CheckBox to a star
RadioButtons in a RadioGroup automatically toggle off when one is selected
CQU - COIT20270 Application Development for Mobile Platforms
6
…Other Basic Views
Use android:orientation=“horizontal” to place RadioButtons horizontally, rather than in the default vertical layout
The android:id of a view is used by View.findViewById() to identify each unique view by its Id
The setOnClickListener() method is used to define a call-back for handling a click on a view
CQU - COIT20270 Application Development for Mobile Platforms
7
ProgressBar View
The ProgressBar view is used to indicate progress of some background task
The default view is indeterminate, merely showing cyclic animation, that you stop when the activity is complete
You hide a ProgressBar by setting its Visibility attribute to View.Gone. This stops the ProgressBar and removes the it from the view
You can change the look of the ProgressBar using the constants: Widget.ProgressBar.Horizontal, Widget.ProgressBar.Small, Widget.ProgressBar.Large, Widget.ProgressBar.Inverse, Widget.ProgressBar.Small.Inverse, Widget.ProgressBar.Large.Inverse
CQU - COIT20270 Application Development for Mobile.
1 Object tracking using sensor network Orla SahiSilvaGraf83
1
Object tracking using sensor network
Orla Sahithi Reddy, email:[email protected]
Abstract—With the help of sensor networks we can keep
track on the events using low and tiny powered devices.
In the paper, we are going to analyze and compare
multiple object tracking methods. Instead of using a
single sensor we use multiple sensors and space them, so
it gives us information. Wireless sensor networks has
node with sensor capabilities and place in object
proximity for detecting them. Sensor networks are
applicable in many fields. Depending on the object
tracking in sensor network ranging from defense and
military applications to earth sciences and
environmental, habitat monitoring, traffic monitoring,
surveillance and military reconnaissance and cross-
border which involves habitat monitoring, infiltration
and other commercial applications.
Index Terms—energy efficient object tracking, object
tracking, quality of tracking, wireless sensor networks,
multi target tracking, routing
I. INTRODUCTION
We Need to have a gathering of frameworks which
cooperate to follow an item rather than a solitary
sensor. Due to this strength, ability and productivity of
the arrangement. Various sensors mitigate the issue of
single purpose of disappointment. A Single costly
sensor expands the danger of disappointment over the
zone of intrigue. Every sensor hub has a sensor ready,
a processor and a remote handset. Normally, a
following application research can be ordered in two
different ways. In recent years, Wireless sensor
network is one of the rapidly growing area[1]. To
begin with, the issue of precisely evaluating the area
of article and second being in organize information
preparing and information conglomeration model for
following item. Article can be situated out commonly
by two activities; by update from the sensors or
questioning the sensor for information to find the item.
Checking of articles would require less time than
following of new item.
Regularly, a remote sensor organize comprises of
enormous number of sensor hubs and is wanted to find
an item in the sensor arrange by playing out a routine
occasionally. This included following the article and
assembling data.
This is a term paper submitted for course requirement fulfillment of
“Advanced Wireless Networks”.
Sahithi Reddy Orla is current student in Wright State University
Computer Science and Engineering Department, Fairborn, OH
45324, USA (e-mail: [email protected], UID: U00916256).
We have to have a particular calculation to process or
track the area of the article with the assistance of
information There are different sorts of item following
strategies which can be looked at and broke down. In
remote sensor systems we have sensor hubs to find an
item in the system. This procedure is done
occasionally including gathering information from
sensor hubs.
There are two sign ...
Intelligent Video Surveillance System using Deep LearningIRJET Journal
This document discusses an intelligent video surveillance system using deep learning. It proposes a framework that first detects abnormal human activity in video streams using an effective CNN model. It then tracks detected individuals throughout the video using an ultra-fast object tracker. Feature extraction is performed on consecutive frames using a CNN, and a deep learning model is trained to recognize and detect activities based on temporal changes in frames. The system aims to allow for quick abnormal activity detection with low computational complexity compared to other methods.
The document discusses sensor cloud, which integrates wireless sensor networks with cloud computing. It allows for the powerful analysis of sensor data through massive cloud infrastructure. The key benefits of sensor cloud include scalability, increased data storage and processing power, dynamic provisioning of services, and automation. Some challenges are implementation costs and maintaining continuous connectivity between sensors and the cloud. The document outlines the general architecture and components of a sensor cloud system and provides examples of applications in transportation monitoring, military use, weather forecasting, and healthcare.
Wearable Gait Classification Using STM SensortileShayan Mamaghani
- Successful and efficient classification of gait behavior.
- Automated real-time discrimination.
- Used STM Sensortile in a dual sensor data acquisition module and a Beaglebone for processing.
- Utilized the FANN neural network library to train and test the system.
The document discusses Android location and sensor APIs. It provides an overview of location services in Android, which allows apps to access location through the LocationManager. It also discusses the sensors framework, which gives access to motion, position, and environment sensors. It describes how to identify available sensors, register listeners to receive sensor events, and handle the sensor data. Key classes like SensorManager, Sensor, and SensorEventListener are also summarized.
The document summarizes an algorithm for object detection and tracking in moving backgrounds under different environmental conditions. The algorithm uses a discriminative learning approach to develop a more robust way of updating an adaptive appearance model. It aims to handle partial occlusions without significant drift and work well with minimal parameter tuning. The algorithm divides each frame into blocks and extracts features using a random Gaussian matrix method. A Gaussian classifier is used to get the tracking location with the highest response. The classifier is incrementally learned and updated using positive and negative samples to predict the object location in the next frame. The proposed algorithm is shown to outperform existing L1-tracker algorithms in terms of accuracy, computational efficiency, and robustness to appearance changes.
IRJET- Human Activity Recognition using Smartphone SensorsIRJET Journal
1. The document describes a human activity recognition system developed by researchers that uses smartphone sensors to recognize activities like walking, running, cycling and still.
2. The system was developed as an Android application using machine learning and connects to a database through XAMP server to display the accuracy of recognized user activities.
3. The application collects sensor data from the phone's accelerometer, gyroscope and other sensors to recognize activities without needing additional wearable devices. It aims to improve the accuracy of activity recognition compared to other systems.
Slides for the presentation given at the Webist 2021 conference
Abstract:
A research team that wants to validate a new IoT solution has to implement a testbed. It is a complex step
since it must provide a realistic environment, and this may require skills that are not present in the team. This
paper explores the requirements of an IoT testbed and proposes an open-source solution based on low-cost
and widely available components and technologies. The testbed implements an architecture consisting of a
collector managing several edge devices. Security levels and duty-cycle are tunable depending on the specific
application. After analyzing the testbed requirements, the paper illustrates a template that uses WiFi for the
link layer, HTTPS for structured communication, an ESP8266 board for edge units, and a RaspberryPi for the
collector.
The extension of the OCCI framework to describe a monitoring infrastructure.
A demo explains how the infrastructure is generated starting from the OCCI specification.
The source of the demo (in Java) is available in the repository of the OCCI working group.
The document discusses several projects related to analyzing data from Fitbit activity monitors. It covers developing APIs to access Fitbit data using OAuth protocols and ensuring data accuracy. It also discusses using Fitbit data for predictive analytics to detect potential depression and comparing Fitbit and treadmill step count data. Machine learning algorithms like SVM and Bayes classification are used for the predictive analytics. Linear regression is used to analyze the relationship between Fitbit and treadmill step counts. The projects aim to better utilize Fitbit data through APIs, analytics and comparing against other activity monitors.
Leveraging Python Telemetry, Azure Application Logging, and Performance Testi...Stackify
In today's fast-paced digital landscape, ensuring the reliability, performance, and observability of applications is crucial. This involves leveraging tools and techniques such as Python telemetry, Azure application logging, and performance testing in production. These practices help in monitoring application health, diagnosing issues, and optimizing performance, ultimately leading to a better user experience and more robust applications. In this PDF, we'll explore these concepts in detail and understand how they can be effectively implemented.
The document describes ObserveIT software that records and replays terminal, Citrix, and console user sessions. It provides key details about the company, product capabilities, customer base, benefits, and technical architecture. Specifically, it allows compliance auditing by tracking all access, remote vendor monitoring, and root cause analysis through playback of exact user actions. The software has a global presence and is deployed across industries for security, compliance, troubleshooting, and SLA validation.
CyberLab Training Division :
Intel VTune Amplifier is a commercial application for software performance analysis for 32 and 64-bit x86 based machines, and has both GUI and command line interfaces. It is available for both Linux and Microsoft Windows operating systems. Although basic features work on both Intel and AMD hardware, advanced hardware-based sampling requires an Intel-manufactured CPU.
Whether you are tuning for the first time or doing advanced performance optimization, Intel® VTune Amplifier provides a rich set of performance insight into CPU & GPU performance, threading performance & scalability, bandwidth, caching and much more. Analysis is faster and easier because VTune Amplifier understands common threading models and presents information at a higher level that is easier to interpret. Use its powerful analysis to sort, filter and visualize results on the timeline and on your source.
It is available as part of Intel Parallel Studio or as a stand-alone product.
VTune Amplifier assists in various kinds of code profiling including stack sampling, thread profiling and hardware event sampling. The profiler result consists of details such as time spent in each sub routine which can be drilled down to the instruction level. The time taken by the instructions are indicative of any stalls in the pipeline during instruction execution. The tool can be also used to analyze thread performance. The new GUI can filter data based on a selection in the timeline.
For More Details.
Visit: http://www.cyberlabzone.com
Creating aggregated Sensu monitors, or how to monitor a group of monitorsMaggie Moreno
This document describes how to create aggregated Sensu monitors by querying logs stored in Elasticsearch. It discusses sending Sensu check logs and outputs to Elasticsearch (steps 1-2), creating a Sensu check called Senseuss that defines an Elasticsearch query and expressions to alert on query results (step 3), and provides examples of using Senseuss.
After a model has been deployed, it's important to understand how the model is being used in production, and to detect any degradation in its effectiveness due to data drift. This module describes tech- niques for monitoring models and their data.
IRJET- Full Body Motion Detection and Surveillance System ApplicationIRJET Journal
1) The document discusses a system for real-time full-body motion detection and surveillance using computer vision techniques.
2) It involves comparing video frames over time to detect motion by treating videos as stacks of frames and looking for differences between frames.
3) The goal is to track body motion in real time using OpenCV for applications like surveillance systems, pose estimation, and other filters.
COIT20270 Application Development for Mobile PlatformsWeek 4.docxmary772
COIT20270 Application Development for Mobile Platforms
Week 4: Designing UI’s with Views
Dr. R. Balsys, CQU, 2012.
Source: Beginning Android Programming with Android Studio, J.F. DiMarzio, 2016
Week 4 – Designing UI’s with Views
Objectives, to understand how to use:
basic views
TextView views
Button, ImageButton, EditText, Checkbox, ToggleButton, RadioButton and RadioGroup views
ProgressBar views
AutoCompleteTextView views
Picker views – TimePicker and DatePicker
CQU - COIT20270 Application Development for Mobile Platforms
Basic Views
Basic views allow you to display text and perform selection. This includes-
TextView
Button
ImageButton
EditText
Checkbox
ToggleButton
RadioButton
RadioGroup
CQU - COIT20270 Application Development for Mobile Platforms
3
TextView view
This basic view allows you to display static text
<TextView> elements are contained in the main.xml file in the res/layout directory
CQU - COIT20270 Application Development for Mobile Platforms
4
Other Basic Views
Other basic views you will use include:
Button – a push button widget
ImageButton – a Button with an image on it
EditText – subclass of TextView with editable text
CheckBox – a button with checked and unchecked states
RadioGroup and RadioButton – RadioGroup is used to group RadioButton’s
ToggleButton – displays states using a light indicator
CQU - COIT20270 Application Development for Mobile Platforms
5
…Other Basic Views
Use “fill_parent” for android:layout_width or android:layout_height so that the basic view fills the parent view space
Use “wrap_content” for android:layout_width or android:layout_height so that the basic view tightly bounds the content only
The android:src value is used to define the image for an ImageButton
You can use the style attribute to set the style of a CheckBox to a star
RadioButtons in a RadioGroup automatically toggle off when one is selected
CQU - COIT20270 Application Development for Mobile Platforms
6
…Other Basic Views
Use android:orientation=“horizontal” to place RadioButtons horizontally, rather than in the default vertical layout
The android:id of a view is used by View.findViewById() to identify each unique view by its Id
The setOnClickListener() method is used to define a call-back for handling a click on a view
CQU - COIT20270 Application Development for Mobile Platforms
7
ProgressBar View
The ProgressBar view is used to indicate progress of some background task
The default view is indeterminate, merely showing cyclic animation, that you stop when the activity is complete
You hide a ProgressBar by setting its Visibility attribute to View.Gone. This stops the ProgressBar and removes the it from the view
You can change the look of the ProgressBar using the constants: Widget.ProgressBar.Horizontal, Widget.ProgressBar.Small, Widget.ProgressBar.Large, Widget.ProgressBar.Inverse, Widget.ProgressBar.Small.Inverse, Widget.ProgressBar.Large.Inverse
CQU - COIT20270 Application Development for Mobile.
1 Object tracking using sensor network Orla SahiSilvaGraf83
1
Object tracking using sensor network
Orla Sahithi Reddy, email:[email protected]
Abstract—With the help of sensor networks we can keep
track on the events using low and tiny powered devices.
In the paper, we are going to analyze and compare
multiple object tracking methods. Instead of using a
single sensor we use multiple sensors and space them, so
it gives us information. Wireless sensor networks has
node with sensor capabilities and place in object
proximity for detecting them. Sensor networks are
applicable in many fields. Depending on the object
tracking in sensor network ranging from defense and
military applications to earth sciences and
environmental, habitat monitoring, traffic monitoring,
surveillance and military reconnaissance and cross-
border which involves habitat monitoring, infiltration
and other commercial applications.
Index Terms—energy efficient object tracking, object
tracking, quality of tracking, wireless sensor networks,
multi target tracking, routing
I. INTRODUCTION
We Need to have a gathering of frameworks which
cooperate to follow an item rather than a solitary
sensor. Due to this strength, ability and productivity of
the arrangement. Various sensors mitigate the issue of
single purpose of disappointment. A Single costly
sensor expands the danger of disappointment over the
zone of intrigue. Every sensor hub has a sensor ready,
a processor and a remote handset. Normally, a
following application research can be ordered in two
different ways. In recent years, Wireless sensor
network is one of the rapidly growing area[1]. To
begin with, the issue of precisely evaluating the area
of article and second being in organize information
preparing and information conglomeration model for
following item. Article can be situated out commonly
by two activities; by update from the sensors or
questioning the sensor for information to find the item.
Checking of articles would require less time than
following of new item.
Regularly, a remote sensor organize comprises of
enormous number of sensor hubs and is wanted to find
an item in the sensor arrange by playing out a routine
occasionally. This included following the article and
assembling data.
This is a term paper submitted for course requirement fulfillment of
“Advanced Wireless Networks”.
Sahithi Reddy Orla is current student in Wright State University
Computer Science and Engineering Department, Fairborn, OH
45324, USA (e-mail: [email protected], UID: U00916256).
We have to have a particular calculation to process or
track the area of the article with the assistance of
information There are different sorts of item following
strategies which can be looked at and broke down. In
remote sensor systems we have sensor hubs to find an
item in the system. This procedure is done
occasionally including gathering information from
sensor hubs.
There are two sign ...
Intelligent Video Surveillance System using Deep LearningIRJET Journal
This document discusses an intelligent video surveillance system using deep learning. It proposes a framework that first detects abnormal human activity in video streams using an effective CNN model. It then tracks detected individuals throughout the video using an ultra-fast object tracker. Feature extraction is performed on consecutive frames using a CNN, and a deep learning model is trained to recognize and detect activities based on temporal changes in frames. The system aims to allow for quick abnormal activity detection with low computational complexity compared to other methods.
The document discusses sensor cloud, which integrates wireless sensor networks with cloud computing. It allows for the powerful analysis of sensor data through massive cloud infrastructure. The key benefits of sensor cloud include scalability, increased data storage and processing power, dynamic provisioning of services, and automation. Some challenges are implementation costs and maintaining continuous connectivity between sensors and the cloud. The document outlines the general architecture and components of a sensor cloud system and provides examples of applications in transportation monitoring, military use, weather forecasting, and healthcare.
Wearable Gait Classification Using STM SensortileShayan Mamaghani
- Successful and efficient classification of gait behavior.
- Automated real-time discrimination.
- Used STM Sensortile in a dual sensor data acquisition module and a Beaglebone for processing.
- Utilized the FANN neural network library to train and test the system.
The document discusses Android location and sensor APIs. It provides an overview of location services in Android, which allows apps to access location through the LocationManager. It also discusses the sensors framework, which gives access to motion, position, and environment sensors. It describes how to identify available sensors, register listeners to receive sensor events, and handle the sensor data. Key classes like SensorManager, Sensor, and SensorEventListener are also summarized.
The document summarizes an algorithm for object detection and tracking in moving backgrounds under different environmental conditions. The algorithm uses a discriminative learning approach to develop a more robust way of updating an adaptive appearance model. It aims to handle partial occlusions without significant drift and work well with minimal parameter tuning. The algorithm divides each frame into blocks and extracts features using a random Gaussian matrix method. A Gaussian classifier is used to get the tracking location with the highest response. The classifier is incrementally learned and updated using positive and negative samples to predict the object location in the next frame. The proposed algorithm is shown to outperform existing L1-tracker algorithms in terms of accuracy, computational efficiency, and robustness to appearance changes.
IRJET- Human Activity Recognition using Smartphone SensorsIRJET Journal
1. The document describes a human activity recognition system developed by researchers that uses smartphone sensors to recognize activities like walking, running, cycling and still.
2. The system was developed as an Android application using machine learning and connects to a database through XAMP server to display the accuracy of recognized user activities.
3. The application collects sensor data from the phone's accelerometer, gyroscope and other sensors to recognize activities without needing additional wearable devices. It aims to improve the accuracy of activity recognition compared to other systems.
Similar to Extending the OCCI API with monitoring capabilities (20)
Slides for the presentation given at the Webist 2021 conference
Abstract:
A research team that wants to validate a new IoT solution has to implement a testbed. It is a complex step
since it must provide a realistic environment, and this may require skills that are not present in the team. This
paper explores the requirements of an IoT testbed and proposes an open-source solution based on low-cost
and widely available components and technologies. The testbed implements an architecture consisting of a
collector managing several edge devices. Security levels and duty-cycle are tunable depending on the specific
application. After analyzing the testbed requirements, the paper illustrates a template that uses WiFi for the
link layer, HTTPS for structured communication, an ESP8266 board for edge units, and a RaspberryPi for the
collector.
Lezione tenuta nel corso di Mobile and Cyber Physical Systems della Laurea Magistrale di Informatica a Pisa.
- Le App per l'integrazione con altri servizi: ThingTweet e ThingHTTPi
- Le App per l'innesco di azioni: TimeControl, TweetControl e React
- Esercizi pratici in Python
Lezione tenuta nel corso di Mobile and Cyber Physical Systems della Laurea Magistrale di Informatica a Pisa.
- Introduzione a ThingSpeak
- Pubblicazione e recupero di dati
- Pubblicazione e recupero di comandi CallBack
- Esercizi pratici in Python
Slides of the presentation at IEEE WiMob/SEUNet 2017, in Rome.
We exploit an overlooked feature of the ESP8266 WiFi chip, i.e. the AT commands interpreter, to implement a sensor/actuator that meets the above specifications. To test our design, we implement a library that provides a transparent wrapper for AT commands. Hardware and software are available on bitbucket.
Collision avoidance using a wandering token in the PTP protocolAugusto Ciuffoletti
Slides presented during the 2010 WIGOWIN Workshop at the Department of Computer Science in Pisa - May 26.
Full paper available at http://eprints.adm.unipi.it
Algorithms based on the circulation of a unique token are often indicated in the coordination of distributed systems. We introduce the design of the token passing operation at application level, that exhibits the requirements of security, since the token is a sensitive resource, and scalability, since the token passing protocol must not implement security at expense of scalability. These
characteristics make our solution suitable for large scale distributed infrastructures.
1) The document describes a "wandering token" approach for coordinating access to shared resources among thousands of agents in a scalable way.
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
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Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
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- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Extending the OCCI API with monitoring capabilities
1. OCCI Monitoring
Augusto Ciuffoletti
OCCI Monitoring
Extending the OCCI API with monitoring capabilities
Augusto Ciuffoletti
Dept. of Computer Science - Univ. of Pisa
September 13, 2013
4. OCCI Monitoring
Augusto Ciuffoletti
Motivation
SLA is a defined target to obtain user confidence
SLA is tightly related with monitoring, so we start from
cloud monitoring
The user may be in its turn a service provider (inside
monitoring)
5. OCCI Monitoring
Augusto Ciuffoletti
Motivation
SLA is a defined target to obtain user confidence
SLA is tightly related with monitoring, so we start from
cloud monitoring
The user may be in its turn a service provider (inside
monitoring)
The user may simply want to verify the quality of the
service (outside monitoring)
6. OCCI Monitoring
Augusto Ciuffoletti
Motivation
SLA is a defined target to obtain user confidence
SLA is tightly related with monitoring, so we start from
cloud monitoring
The user may be in its turn a service provider (inside
monitoring)
The user may simply want to verify the quality of the
service (outside monitoring)
In both cases, the user needs the tools to define
resource monitoring
7. OCCI Monitoring
Augusto Ciuffoletti
Motivation
SLA is a defined target to obtain user confidence
SLA is tightly related with monitoring, so we start from
cloud monitoring
The user may be in its turn a service provider (inside
monitoring)
The user may simply want to verify the quality of the
service (outside monitoring)
In both cases, the user needs the tools to define
resource monitoring
Keep into account the case of a composite service
(many providers)
8. OCCI Monitoring
Augusto Ciuffoletti
Motivation
SLA is a defined target to obtain user confidence
SLA is tightly related with monitoring, so we start from
cloud monitoring
The user may be in its turn a service provider (inside
monitoring)
The user may simply want to verify the quality of the
service (outside monitoring)
In both cases, the user needs the tools to define
resource monitoring
Keep into account the case of a composite service
(many providers)
A simple API aligned with OCCI
11. OCCI Monitoring
Augusto Ciuffoletti
Basic functions
Monitoring is made of three basic activities
extract operational parameters from a Resource
gather the operational parameters to obtain the
measure of a metric of interest
12. OCCI Monitoring
Augusto Ciuffoletti
Basic functions
Monitoring is made of three basic activities
extract operational parameters from a Resource
gather the operational parameters to obtain the
measure of a metric of interest
deliver the measurement to the relevant party
14. OCCI Monitoring
Augusto Ciuffoletti
Aggregate and deliver
Distiguished activities that need the provision of
computing, storage, networking resources
Tightly integrated, under control of the provider
15. OCCI Monitoring
Augusto Ciuffoletti
Aggregate and deliver
Distiguished activities that need the provision of
computing, storage, networking resources
Tightly integrated, under control of the provider
Candidate for the introduction of a new kind of
resource: the Sensor
16. OCCI Monitoring
Augusto Ciuffoletti
Aggregate and deliver
Distiguished activities that need the provision of
computing, storage, networking resources
Tightly integrated, under control of the provider
Candidate for the introduction of a new kind of
resource: the Sensor
The user that wants to exert monitoring instantiates
(and pays for) a Sensor
17. OCCI Monitoring
Augusto Ciuffoletti
Aggregate and deliver
Distiguished activities that need the provision of
computing, storage, networking resources
Tightly integrated, under control of the provider
Candidate for the introduction of a new kind of
resource: the Sensor
The user that wants to exert monitoring instantiates
(and pays for) a Sensor
Note: a cost is associated to the Sensor, although this
is not explicit in the definition of monitoring
20. OCCI Monitoring
Augusto Ciuffoletti
Basic functions
The monitoring function is controlled by time
The native attributes of a Sensor are:
How frequently it produces a new measurement
21. OCCI Monitoring
Augusto Ciuffoletti
Basic functions
The monitoring function is controlled by time
The native attributes of a Sensor are:
How frequently it produces a new measurement
During which time lapse it performs the measurements
22. OCCI Monitoring
Augusto Ciuffoletti
Basic functions
The monitoring function is controlled by time
The native attributes of a Sensor are:
How frequently it produces a new measurement
During which time lapse it performs the measurements
Too many variants for aggregation/delivery:
OCCI-mixins
23. OCCI Monitoring
Augusto Ciuffoletti
Basic functions
The monitoring function is controlled by time
The native attributes of a Sensor are:
How frequently it produces a new measurement
During which time lapse it performs the measurements
Too many variants for aggregation/delivery:
OCCI-mixins
Mixins are classified using tags (sort of subtyping)
25. OCCI Monitoring
Augusto Ciuffoletti
Extract measurements
This is an ability that a sensor has with respect to a real
resource
Capability of extracting measurements (e.g., through
resource instrumentation)
26. OCCI Monitoring
Augusto Ciuffoletti
Extract measurements
This is an ability that a sensor has with respect to a real
resource
Capability of extracting measurements (e.g., through
resource instrumentation)
This is represented as a collector link from the sensor to
the resource
27. OCCI Monitoring
Augusto Ciuffoletti
Extract measurements
This is an ability that a sensor has with respect to a real
resource
Capability of extracting measurements (e.g., through
resource instrumentation)
This is represented as a collector link from the sensor to
the resource
The generic attributes of a collector correspond to the
sampling period:
28. OCCI Monitoring
Augusto Ciuffoletti
Extract measurements
This is an ability that a sensor has with respect to a real
resource
Capability of extracting measurements (e.g., through
resource instrumentation)
This is represented as a collector link from the sensor to
the resource
The generic attributes of a collector correspond to the
sampling period:
The sampling period
29. OCCI Monitoring
Augusto Ciuffoletti
Extract measurements
This is an ability that a sensor has with respect to a real
resource
Capability of extracting measurements (e.g., through
resource instrumentation)
This is represented as a collector link from the sensor to
the resource
The generic attributes of a collector correspond to the
sampling period:
The sampling period
The accuracy of the sampling period
30. OCCI Monitoring
Augusto Ciuffoletti
Extract measurements
This is an ability that a sensor has with respect to a real
resource
Capability of extracting measurements (e.g., through
resource instrumentation)
This is represented as a collector link from the sensor to
the resource
The generic attributes of a collector correspond to the
sampling period:
The sampling period
The accuracy of the sampling period
OCCI-mixins are introduced to specify the measurement
technique used
31. OCCI Monitoring
Augusto Ciuffoletti
Mixin sub-typing: the tags
According with the OCCI core specification a mixin with
no attributes (a tag) can be associated to another mixin
as a sort of label
32. OCCI Monitoring
Augusto Ciuffoletti
Mixin sub-typing: the tags
According with the OCCI core specification a mixin with
no attributes (a tag) can be associated to another mixin
as a sort of label
Syntactic and semantic restrictions can be introduced
for mixins with a certain label, thus supporting a
specification
33. OCCI Monitoring
Augusto Ciuffoletti
Mixin sub-typing: the tags
According with the OCCI core specification a mixin with
no attributes (a tag) can be associated to another mixin
as a sort of label
Syntactic and semantic restrictions can be introduced
for mixins with a certain label, thus supporting a
specification
By defining tagged mixins, the provider describes the
monitoring capabilities offered to the user
34. OCCI Monitoring
Augusto Ciuffoletti
Mixin sub-typing: the tags
According with the OCCI core specification a mixin with
no attributes (a tag) can be associated to another mixin
as a sort of label
Syntactic and semantic restrictions can be introduced
for mixins with a certain label, thus supporting a
specification
By defining tagged mixins, the provider describes the
monitoring capabilities offered to the user
Next slides describe three such tags:
35. OCCI Monitoring
Augusto Ciuffoletti
Mixin sub-typing: the tags
According with the OCCI core specification a mixin with
no attributes (a tag) can be associated to another mixin
as a sort of label
Syntactic and semantic restrictions can be introduced
for mixins with a certain label, thus supporting a
specification
By defining tagged mixins, the provider describes the
monitoring capabilities offered to the user
Next slides describe three such tags:
metric specific for collector links
36. OCCI Monitoring
Augusto Ciuffoletti
Mixin sub-typing: the tags
According with the OCCI core specification a mixin with
no attributes (a tag) can be associated to another mixin
as a sort of label
Syntactic and semantic restrictions can be introduced
for mixins with a certain label, thus supporting a
specification
By defining tagged mixins, the provider describes the
monitoring capabilities offered to the user
Next slides describe three such tags:
metric specific for collector links
aggregator specific for sensor resources
37. OCCI Monitoring
Augusto Ciuffoletti
Mixin sub-typing: the tags
According with the OCCI core specification a mixin with
no attributes (a tag) can be associated to another mixin
as a sort of label
Syntactic and semantic restrictions can be introduced
for mixins with a certain label, thus supporting a
specification
By defining tagged mixins, the provider describes the
monitoring capabilities offered to the user
Next slides describe three such tags:
metric specific for collector links
aggregator specific for sensor resources
publisher specific for sensor resources
39. OCCI Monitoring
Augusto Ciuffoletti
The metric tag
The tag metric is associated with a measurement
technique, and is related with a collector link;
The mixin that has the metric tag has the following
attributes:
40. OCCI Monitoring
Augusto Ciuffoletti
The metric tag
The tag metric is associated with a measurement
technique, and is related with a collector link;
The mixin that has the metric tag has the following
attributes:
metric attribute strings that are used as an identifier to
refer to the output measurement stream
41. OCCI Monitoring
Augusto Ciuffoletti
The metric tag
The tag metric is associated with a measurement
technique, and is related with a collector link;
The mixin that has the metric tag has the following
attributes:
metric attribute strings that are used as an identifier to
refer to the output measurement stream
control attributes used to control the measurement
process (e.g. packet length of a ping)
42. OCCI Monitoring
Augusto Ciuffoletti
The aggregator tag
the tag aggregator is associated with a mixin that
implements an algorithm for monitoring data
aggregation
43. OCCI Monitoring
Augusto Ciuffoletti
The aggregator tag
the tag aggregator is associated with a mixin that
implements an algorithm for monitoring data
aggregation
an aggregator mixin is related with a sensor resource
44. OCCI Monitoring
Augusto Ciuffoletti
The aggregator tag
the tag aggregator is associated with a mixin that
implements an algorithm for monitoring data
aggregation
an aggregator mixin is related with a sensor resource
the mixin with the aggregator tag are characterized by:
45. OCCI Monitoring
Augusto Ciuffoletti
The aggregator tag
the tag aggregator is associated with a mixin that
implements an algorithm for monitoring data
aggregation
an aggregator mixin is related with a sensor resource
the mixin with the aggregator tag are characterized by:
input attributes strings that are used as an identifier to
refer to input measurement streams
46. OCCI Monitoring
Augusto Ciuffoletti
The aggregator tag
the tag aggregator is associated with a mixin that
implements an algorithm for monitoring data
aggregation
an aggregator mixin is related with a sensor resource
the mixin with the aggregator tag are characterized by:
input attributes strings that are used as an identifier to
refer to input measurement streams
control attributes that are parameters for the
aggregation function (e.g. the gain in an
EWMA)
47. OCCI Monitoring
Augusto Ciuffoletti
The aggregator tag
the tag aggregator is associated with a mixin that
implements an algorithm for monitoring data
aggregation
an aggregator mixin is related with a sensor resource
the mixin with the aggregator tag are characterized by:
input attributes strings that are used as an identifier to
refer to input measurement streams
control attributes that are parameters for the
aggregation function (e.g. the gain in an
EWMA)
metric attributes strings that are used as an identifier to
refer to the output measurement stream
48. OCCI Monitoring
Augusto Ciuffoletti
The publisher tag
the tag publisher is associated with a mixin that
implements a technique to deliver the data outside the
monitoring infrastructure
49. OCCI Monitoring
Augusto Ciuffoletti
The publisher tag
the tag publisher is associated with a mixin that
implements a technique to deliver the data outside the
monitoring infrastructure
a publisher mixin is related with a sensor resource
50. OCCI Monitoring
Augusto Ciuffoletti
The publisher tag
the tag publisher is associated with a mixin that
implements a technique to deliver the data outside the
monitoring infrastructure
a publisher mixin is related with a sensor resource
the mixin with a publisher tag are characterized by:
51. OCCI Monitoring
Augusto Ciuffoletti
The publisher tag
the tag publisher is associated with a mixin that
implements a technique to deliver the data outside the
monitoring infrastructure
a publisher mixin is related with a sensor resource
the mixin with a publisher tag are characterized by:
input attribute a string that is used as an identifier to
refer to input measurement stream
52. OCCI Monitoring
Augusto Ciuffoletti
The publisher tag
the tag publisher is associated with a mixin that
implements a technique to deliver the data outside the
monitoring infrastructure
a publisher mixin is related with a sensor resource
the mixin with a publisher tag are characterized by:
input attribute a string that is used as an identifier to
refer to input measurement stream
control attributes that are parameters for the publishing
function (e.g. the UDP port that is used
for streaming)
54. OCCI Monitoring
Augusto Ciuffoletti
The role of metric and input attributes
they describe the flow of monitoring data
their values are unique identifiers in a scope
corresponding to a sensor and all outgoing collectors
55. OCCI Monitoring
Augusto Ciuffoletti
The role of metric and input attributes
they describe the flow of monitoring data
their values are unique identifiers in a scope
corresponding to a sensor and all outgoing collectors
the provider is free to implement the transport of the
measurement stream in the most convenient way
57. OCCI Monitoring
Augusto Ciuffoletti
Shortcuts for simple use cases
here metric mixin, can be associated directly to the
monitored resource and has a web service interface
a tagged mixin can be associated with a generic
resource or link, avoiding the definition of a sensor or
collector
58. OCCI Monitoring
Augusto Ciuffoletti
Shortcuts for simple use cases
here metric mixin, can be associated directly to the
monitored resource and has a web service interface
a tagged mixin can be associated with a generic
resource or link, avoiding the definition of a sensor or
collector
shortcuts effectively help very simple use cases, but are
generally a source of inefficiency and complexity
74. OCCI Monitoring
Augusto Ciuffoletti
Also in the document
Conformance profiles: to accomodate the presence of
providers that do not implement a monitoring interface
75. OCCI Monitoring
Augusto Ciuffoletti
Also in the document
Conformance profiles: to accomodate the presence of
providers that do not implement a monitoring interface
Security issues
76. OCCI Monitoring
Augusto Ciuffoletti
Also in the document
Conformance profiles: to accomodate the presence of
providers that do not implement a monitoring interface
Security issues
A detailed example using the http rendering
77. OCCI Monitoring
Augusto Ciuffoletti
Also in the document
Conformance profiles: to accomodate the presence of
providers that do not implement a monitoring interface
Security issues
A detailed example using the http rendering
...and several bugs.
78. OCCI Monitoring
Augusto Ciuffoletti
Also in the document
Conformance profiles: to accomodate the presence of
providers that do not implement a monitoring interface
Security issues
A detailed example using the http rendering
...and several bugs.
That’s all...