This document provides redacted examples of how customers have used AMI solutions while protecting private customer data. The examples are organized into sections on planning, utilization, project performance, MS Project dashboards, SLAs, human resources, pharmaceuticals, and other use cases. Numeric values and names have been altered to maintain customer confidentiality in the examples.
This short note describes a relatively simple methodology, procedure or approach to increase the performance of already installed industrial models used for optimization, control, simulation and/or monitoring purposes. The method is called Excess or X-Model Regression (XMR) where the concept of “excess modeling” or an X-model is taken from the field of thermodynamics to describe the departure or residual behaviour of real (non-ideal) gases and liquids from their ideal state (Kyle, 1999; Poling et. al., 2001; Smith et. al., 2001). It has also been applied to model the non-ideal or nonlinear behaviour of blending motor gasoline octanes with its synergistic and antagonistic interactional effects (Muller, 1992).
The fundamental idea of XMR is to calibrate, train, fit or estimate, using actual data and multiple linear regression (MLR) or ordinary least squares (OLS), the deviations of the measured responses from the existing model responses. The existing model may be a glass, grey or black-box model (known or unknown, linear or nonlinear, implicit/open or explicit/closed) depending on the use of the model. That is, for optimization and control the model structure and parameters are available given that derivative information is required although for simulation and monitoring, the model may only be observed through the dependent output variables given the necessary independent input variables.
[whitepaper] Cellular Technology simplifies Smart Water Meter Deployments Orange Business Services
Sierra Wireless and Orange Business Services are ready to partner with OEMs and utilities
building the new generation of smart water metering technology. Providing fl exible hardware,
strong security, and a comprehensive device-to-cloud solution, a joint solution from Sierra
Wireless and Orange can help OEMs capitalize on this growing global market and help
optimize the world’s water supply.
Martin anda h2ome smart meter trial 150213Martin Anda
Presented at ICT4S 2013, the First International Conference on Information and Communication Technologies for Sustainability, held in Zurich, February 2013, http://www.ict4s.org
advanced metering infrastructure, advanced meter reading, internet of Things, WiMax, LTE, smart meter analytics, smart meter communication technologies, LTE advanced, WiFi, smart meter architectural blueprint
More details: (blog: http://sandyclassic.wordpress.com ,
linkedin: ie.linkedin.com/in/sandepsharma/)
EC2 AMI Factory with Chef, Berkshelf, and PackerGeorge Miranda
Presentation accompanying a Live Demo at the AWS Pop-Up Loft in San Francisco on using Chef + Berks + Packer to create an AWS EC2 AMI Factory.
Demo Repo available here -- https://github.com/gmiranda23/chef-ami-factory
This short note describes a relatively simple methodology, procedure or approach to increase the performance of already installed industrial models used for optimization, control, simulation and/or monitoring purposes. The method is called Excess or X-Model Regression (XMR) where the concept of “excess modeling” or an X-model is taken from the field of thermodynamics to describe the departure or residual behaviour of real (non-ideal) gases and liquids from their ideal state (Kyle, 1999; Poling et. al., 2001; Smith et. al., 2001). It has also been applied to model the non-ideal or nonlinear behaviour of blending motor gasoline octanes with its synergistic and antagonistic interactional effects (Muller, 1992).
The fundamental idea of XMR is to calibrate, train, fit or estimate, using actual data and multiple linear regression (MLR) or ordinary least squares (OLS), the deviations of the measured responses from the existing model responses. The existing model may be a glass, grey or black-box model (known or unknown, linear or nonlinear, implicit/open or explicit/closed) depending on the use of the model. That is, for optimization and control the model structure and parameters are available given that derivative information is required although for simulation and monitoring, the model may only be observed through the dependent output variables given the necessary independent input variables.
[whitepaper] Cellular Technology simplifies Smart Water Meter Deployments Orange Business Services
Sierra Wireless and Orange Business Services are ready to partner with OEMs and utilities
building the new generation of smart water metering technology. Providing fl exible hardware,
strong security, and a comprehensive device-to-cloud solution, a joint solution from Sierra
Wireless and Orange can help OEMs capitalize on this growing global market and help
optimize the world’s water supply.
Martin anda h2ome smart meter trial 150213Martin Anda
Presented at ICT4S 2013, the First International Conference on Information and Communication Technologies for Sustainability, held in Zurich, February 2013, http://www.ict4s.org
advanced metering infrastructure, advanced meter reading, internet of Things, WiMax, LTE, smart meter analytics, smart meter communication technologies, LTE advanced, WiFi, smart meter architectural blueprint
More details: (blog: http://sandyclassic.wordpress.com ,
linkedin: ie.linkedin.com/in/sandepsharma/)
EC2 AMI Factory with Chef, Berkshelf, and PackerGeorge Miranda
Presentation accompanying a Live Demo at the AWS Pop-Up Loft in San Francisco on using Chef + Berks + Packer to create an AWS EC2 AMI Factory.
Demo Repo available here -- https://github.com/gmiranda23/chef-ami-factory
The state of Georgia is a valued Computer Aid, Inc. (CAI) customer who is seeing great success with both APO and PPM. From their Director of Enterprise Governance and Planning,
"The CAI solution provides a governance layer of process discipline, best practices, and predictive analysis to reduce risk and improve project success, regardless of the PPM tool used by agency project teams."
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.
The state of Georgia is a valued Computer Aid, Inc. (CAI) customer who is seeing great success with both APO and PPM. From their Director of Enterprise Governance and Planning,
"The CAI solution provides a governance layer of process discipline, best practices, and predictive analysis to reduce risk and improve project success, regardless of the PPM tool used by agency project teams."
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
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
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
AMI example screen shots
1. AMI Customer Solution Examples
These examples have been redacted in a variety
of ways to protect customer data. Numeric
values have been changed, and names have either
been blurred out or changed entirely. In any
examples where whole numbers or names are
represented, those values have been altered
significantly.
DISCLAIMER: These examples have been redacted in a variety of ways to protect customer data. Numeric values have been changed, and names have either been blurred out or changed entirely. In any examples where whole numbers or names are represented, those values have been altered significantly.
This tab represents current performance of 6 selected “key” KPIs, as well as average performance over time for the past 3 months. This is a division-level look at data from many projects, and can be drilled into by levels of the organization. Results are a combination of operational data from external systems and risk associated with contextual data from surveys.
This scorecard represents a portfolio view of several projects, with focus on several selected KPIs. The portfolio can be reorganized to sort by risk associated with any of the available KPIs. This solution is delivered at a 100-150 person IT shop with a nearly even split between on-shore and off-shore resources.
This screen represents a slightly more detailed view of project performance, including performance trends over time by reporting period (in this case, the customer assesses teams twice a month).
This tab represents results of a large (several thousand) satisfaction survey with helpdesk support across the organization. Data is sorted by department and physical geography, and results are anonymous. This solution is deployed at a large organization managing IT projects staffed by 400-500 individuals (per project). They are distributed across the continental US.
This implementation collects resource utilization data from several time/effort tracking systems and consolidates results, making the data reportable by project, role, or individual (both current utilization, and totals over time). This customer is a state government agency with an IT staff over 500.
This engagement represents planned vs. actual hours at a high level, along with status against milestones (all data in this example is derived from survey results)
In a different view of utilization, this instance represents forthcoming demand based on planned activities. Status (and delays) of current activities, coupled with forthcoming projects, presents total capacity and demand, filterable by date (results are combination of survey responses for current project status, along with imported data for time-on-task and pipeline). In this example, results are limited to 3 months in the future, but that is an artificial limit posed by the user.
At a more detailed level, staff count “swells” are shown over time to identify changes in projects with high resource consumption. Specific “key” metrics are also teased out as significant criteria to watch over time – any downward trending results in warnings.
Satisfaction is reported as a purely survey-based representation of data. Summary results of satisfaction on 6 criteria are reported, with the ability to drill down by role, portfolio, organization, or project. Results are reported over time as well as current status.
This implementation uses project plan data to plot degree of project completion over time, then also trends actuals as reported by the team via surveys to represent likelihood of completing on time. When the probable completion date extends beyond the planned date, the message text turns red and projects a new delivery date. Adjusting the date then turns the warning off. This deployment covers a large engagement managing many vendors for a single project – all constituents are rolled together to represent one overall picture of project status.
This screen represents relatively straightforward EVA data, in this example fed by an external financials spreadsheet. Data could come into the system via surveys or a direct feed as well.
This implementation is tracking ticket closure by month – reporting on overall resolution rates, and total open/closed within the month. In this example, the customer wants to show projects in the list even if they do not have any tickets to report for the month (normal behavior would be to show only the projects with tickets in the latest month displays). Totals are then rolled up to report over time, showing incidents by project, as well as overall for the entire organization. In this example, data is completely fed by an external system.
This example is a representation of external data evaluated against expectation guidelines and showing overall performance over the life of a project.
This is another representation of SLA-based data over time, broken out as a percentage. This particular customer wanted a decimal-based representation in order to align with other status reports already in place.
This tab allows a user to evaluate total participation in qualitative data collection, which can be represented by role, assessment, respondent, organization, or project. At a glance, a user can evaluate their overall confidence in data being reported back to them.
This screen represents a report-style summary of responses to assessments, broken out by phase.
The “standard” question response tab allows a user to consume distribution statistics for each question, and drill down by response, respondent, role, project, organization, or date. It also represents distribution of responses over time.
An alternative interpretation of the question response tab for a customer who wanted to be able to put specific emphasis on variation in response distribution from one week to the next.