Tag: digital service desk ai software

Autonomous Things

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Machine learning service provider

Bindu Vijayan

“Autonomous things (AuT), or the Internet of autonomous things (IoAT), is an emerging term for the technological developments that are expected to bring computers into the physical environment as autonomous entities without human direction, freely moving and interacting with humans and other objects…”

To put it simply, Autonomous Things use AI and work unsupervised to complete specific tasks without humans. Devices are enhanced with AI, sensors and analytical capabilities to be able to make informed and appropriate decisions.  They (these devices) work collaboratively between humans and the environment and provide superior performance.  Today AuT work across several environments with various levels of intelligence and capabilities. Some popular examples of these devices are drones, vehicles, smart home devices among others. The components of Autonomous things – software and AI hardware are getting increasingly efficient. With improved technologies (and significantly reducing sensor costs), the variety of tasks and processes that can be automated are increasing, with the advantage of bringing in more data and feedback that can efficiently improve and enhance the benefits of autonomous things.

The technology is used in a wide variety of scenarios – as data collectors from a variety of terrains and environments, as delivery systems (by Amazon, pizza deliveries, etc.), medical supplies to remote areas, etc. Robotics used in the supply chain has proven it reduces/elevates the danger out of the hitherto human tasks in warehouses.  And they probably have the most economic potential currently, followed by autonomous vehicles.  Drones are used to collect data across a wide variety of functions –  for surveillance, security, stock management, weather forecasting, obtaining air data, oceanic data, agricultural planning, etc.

Some fascinating use cases:

Healthcare

Drones are proving to be more and more effective in several ways – they are currently used extensively for surveillance of disaster sites that have biological hazards.  There is no better relevance than the current times when they can actually be used in epidemiology to track disease spread,  and of course for further research and studies.  Drones are facilitating on-demand healthcare by providing medicines to terrains that are difficult to access.  Swoop Aero is one such company that provides medicines via drones.  Drones have brought healthcare into the most remote areas with diagnosis and treatment made available. Remote areas of Africa have their regular medical supplies,  vaccine supplies, lab samples collected, emergency medical equipment made available through Drones. They are also used in telementoring, for perioperative evaluation and so on.  Drones have been very efficient in accessing areas and providing necessary support where ground transport is not reliable or safe or impossible.  Today, most governments have Drones on their national agenda under various sectors. The Delft University of Technology is developing an ambulance drone technology that can be used at disaster sites to increase rescue rates..

Retail

In a world where we have virtual assistants do grocery shopping, replenish stocks, and cooking machines making food, when there is a need to go out shopping, shoppers want to have an easy, fast and frictionless process.  Today, customers do not want to wait in queues and go through conventional checkouts, and Retailers know that they might be losing customers due to their checkout process.  And autonomous shops like Amazon Go are giving that experience to customers where they can purchase without the inconvenience of checkout lines.

Providers of checkout-free shopping technology like ‘Grabango’, use sensor vision and ML to actually hold a virtual shopping basket for every person in the store.  The technology is reputed to process a multitude simultaneous checkout transactions. “Grabango’s system uses high-quality sensor hardware and high-precision computer algorithms to acquire the location of every item in the store. This results in a real-time planogram covering the entire retail environment.” They say it results in increased sales and loyalty, streamlined operations and inventory management and out of stock alerts.

Construction

Companies like Chicago based, Komatsu American Corp., have autonomous haulage stems that have optimized safety in the mining industry like never before. They “help you continue to meet your bottom line while achieving zero-harm” while their focus has been on developing autonomous mining solutions, they have been doing it for more than three decades now! Their FrontRunner AHS has moved more than two billion tons of surface material so far in driverless operations.  Catepillar would be deploying their fleet of autonomous trucks and blast drills for the iron mine in Western Australia – Rio Tinto Koodaideri.  The industry is thriving with autonomous and semi autonomous equipment, and it is evident that it has brought improvements to productivity, and increased profitability. At the Australian mine “autonomous vehicles operated on average 700 hours longer and with 15 per cent lower unit costs”… Similarly, there are other companies like Intsite, a heavy machinery company; their autonomous crane ÁutoSite 100’ does autonomous operation of heavy machinery.

Transportation

Most of us think Tesla when we think autonomous vehicles.  Elon Musk’s dream of providing autonomous ride-sharing has Tesla working on getting out one million robotaxis on the road this year. We will have to wait and see how that is going to pan out. Though autonomous vehicles are the most popular, I suppose it might take a little more time before it finds answers to the regulatory challenges, definitely not an easy task.  It gets quite overwhelming when we think of what we are expecting from autonomous vehicles – it assumes correct performance no matter the uncertainties on the roads and the environment, as well as the ability to face any sort of system failures on its own, and AI is a very critical technology when we are talking real-time decision making. Those sort of scenarios call for a strong computing platform in order to do the analysis at the edge for faster decision making.  The new V2X, which is the 5G vehicle-to-everything is expected to make autonomous vehicles mainstream because the vital information would get transmitted as structured data to the vehicle. V2X is expected to have vehicles interfacing with anything, be it pedestrians, roadside infrastructure, cyclists, etc.

Today, technology is also looking at ‘vehicle platooning’ – “Platoons decrease the distances between cars or trucks using electronic, and possibly mechanical, coupling. This capability would allow many cars or trucks to accelerate or brake simultaneously. This system also allows for a closer headway between vehicles by eliminating reacting distance needed for human reaction.” It has a group of self driving vehicles moving at high speed but safely, as the trucks are in constant communication with each other and use this intelligence to make informed decisions like braking, speeds, etc.  And autonomous trucks and cars can automatically join these platoons or leave, this has the advantages of reduced congestion, fewer traffic collisions, better fuel economy, and shorter commutes during peak hours. 

Conclusion

Studies show that Autonomous things are fast moving to ‘swarm’ or a bunch of intelligent devices, where multiple devices will function together collaboratively, as against the previously isolated intelligent components/ things. They are going to be intelligently networked among themselves and with the environment, and the wider that becomes within every industry, they are going to show phenomenal capabilities. But let’s not forget there is a whole other side to AI, given how unpredictable things are in life, AI would sooner or later have to respond to things that it never saw in training… we still are the smarter ones…

References:

https://en.wikipedia.org/wiki/Autonomous_things

https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2020/

https://worldline.com/en/home/blog/2020/march/from-automatic-to-autonomous-payments-can-things-pay.html

https://en.wikipedia.org/wiki/Self-driving_car

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6174005/

https://www.komatsuamerica.com/

https://en.wikipedia.org/wiki/Platoon_(automobile)https://grabango.com/

Dashboard SAP Lumira Designer – Write Back Functionality

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Mohammed Fazal Uddin Kashif

Dashboards are considered to be one of the key success factors of businesses. Easy access to real-time KPIs allows them to be proactive and address business challenges before they impact the bottom line.

SAP Lumira Designer, formerly known as SAP Design Studio, is one of the robust products available in the market for developing top-of-the-line analytical applications and business dashboards. However, every tool by its core functionality has limitations for some use cases and business processes. One of such considerable cases is the ability to write back to a database directly from the dashboard.

Write back functionality assists business users to modify the data while analyzing from the dashboard rather than doing it in the source system. This functionality facilitates business users to manipulate the data and reflects refreshed data in the dashboard for further review and assessment.

This article introduces the use of Lumira SDK Extension component, POST RESPONSE PARSER, which enables the core range of Lumira designer to expand its boundary to include write-back functionality by integrating external Web API into the Lumira Dashboard.

Integrating Post Response Parser SDK Extension, the Lumira dashboard could be transformed from a pure data visualization application into an interactive data management analytical application.

Data Exploration & Smart Visualizations

Dashboards are analytical tools that visually track, analyzes and display Key Performance Indicators (KPIs) to the business processes or the portfolios. It provides a comprehensive snapshot of the performance of a key component within the portfolio. KPIs are business metrics which assists the leadership team to arrive at key decisions and drive towards the goals.

Business Dashboards and analytical applications provide at-a-glance visual and graphical representation of data which eliminates the need to go through long and complex excel spreadsheets.

Also, it’s time-consuming and difficult to pull out the most important business information whereas presenting that information in an appealing, visual way is more result-driven and effective.

Interactive dashboards enable us to visualize the data, filter on demand and simply click to dive deeper, quickly engage end-users, and provide an intuitive experience and insights.

Among various visualization tools available in the market, SAP Lumira has an edge being an SAP tool where end-user consumption of analytical applications is governed and secured by the SAP Business Objects BI Platform.

Extending the Dashboard Functionality

Lumira designer provides extensive customizations through scripting, styling with CSS and above all, the integration of external SDK Components makes it a pinnacle tool to achieve the desired functionalities.

Like any other technology, dashboards are constantly evolving, with versatility and impactful ability of integrating SDK components assisting the rapidly developing scope and scale of visualizations for the organizations.

Along those lines, Business users expect the ability to modify the data that lies behind a visualization component by providing data inputs to the dashboard while analyzing the data and anticipate the changes to be reflected immediately in the dashboard.

Lumira designer leverages support for updating or modifying the data in underlying database through write back functionality.

Benefits of write back in the dashboard:

  • It transforms a traditional dashboard to Interactive analytical application which supports business data modifications
  • It allows data analysis and data update from the same dashboard, rather switching over different applications for each task

SDK Extensions

SDK stands for Software Development Kit. SDK is set of tools, libraries, code samples, processes and guides that allows developers to create applications on a specific platform.

SDK Extension components can be integrated flawlessly into the core application to utilize its features for the customized product developments. The visualization of extension components is based on HTML, JavaScript and CSS.

Web Application Programming Interface

Web API is an Application Programming Interface over the web which can be accessed using HTTP protocol.

Web API is an extensible framework for building HTTP based services that can be accessed in different applications on different platforms such as web, windows, mobile etc.

Integrating Web APIs into the Lumira designer enhances the dashboard functionality by adding abilities not offered in the baseline version of the tool, such as providing the possibility of writing back to the source database directly from the dashboard itself.

Post Response Parser

Post Response Parser is an SDK Extension, with which you can model your application to make AJAX (Asynchronous JavaScript and XML) calls to any Web API and evaluate the response for desired interactivity in Lumira designer.

Feature of Post Response Parser:

  • Opens a request via AJAX call to any specific URL
  • Accepts parameters along the Request
  • Supports BIAL (BI Action Language) Scripting for interactive control at runtime

Business Use Case

In Banking, Credit Control & Monitoring department uses exception reports on their day to day operations for the analysis of their customers credit performance. Based on the outcomes, the team decides on the action to be taken for the respective customers with the various levels of audits.

Business Team faces challenges to maintain and track the remarks and comments on each customer by looking at the reports. So CCM wants to develop a dashboard with the ability to update their observations and comments on the same dashboard which in turn gets stored in database.

Lumira designer provides sub-optimal workarounds for capturing the filters and remarks with technical components like Bookmarks and Comments which comes along with the core application, but these components cannot not write back to the database, but incorporating  SDK Extensions along with the core would be able to achieve the desired customization in the dashboard application.

Functionality and Process Flow

The Post Response parser integrates external Web API into the Lumira designer, this SDK extension passes the parameters from the dashboard to the underlying stored procedure in Web API which in turn updates to the database.

Snippet of process to be followed:

  • Install Post Response Parser SDK Extension at client and server system
  • Encapsulate the parameters as global variable and enable its property to expose as URL Parameter
  • Create a Web service for dashboard to accommodate the database updates
  • Define an event to trigger the SDK Extension in Lumira application
  • Reload the data source through script to reflect the changes in dashboard

Conclusion

Lumira designer is competent to build Business Intelligence Applications that can be dynamic and customizable as per the business users’ workflow.

An interactive prototype is the best way for both users and designers to learn about their specific needs.

In conclusion, Lumira Designer with SDK Extensions offers that capabilities to accommodate our design process and it stands strong in its ability to build simple or complex Analytic Applications and Executive Dashboards.

About the Author:

Kashif is a SAP Business objects consultant and a business analytics enthusiast. He believes “Ultimate goal is not about winning, but to reach within the depth of capabilities and to compete against yourself to be better than what you are today.”

Discover, Monitor, Analyze & Predict COVID-19

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Bargunan Somasundaram

“Uber, the world’s largest taxi company, owns no vehicles. Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. Netflix, the world’s largest movie house, own no cinemas. And Airbnb, the world’s largest accommodation provider, owns no real estate. Something interesting is happening.”

– Tom Goodwin, an executive at the French media group Havas.

This new breed of companies is the fastest growing in history because they own the customer interface layer. It is the platform where all the value and profit is. “Platform business” is a more wholesome term for this model for which data is the fuel; Big Data & AI/ML technologies are the harbinger of new waves of productivity growth and innovation.

With Big data and AI/ML is making a big difference in the area of public health, let’s see how it is helping us tackle the global emergency of coronavirus formally known as COVID-19.

DISCOVERING / DETECTING

Chinese technology giant Alibaba has developed an AI system for detecting the COVID-19 in CT scans of patients’ chests with 96% accuracy against viral pneumonia cases. It only takes 20 seconds for the AI to decide, whereas humans generally take about 15 minutes to diagnose the illness as there can be upwards of 300 images to evaluate. The system was trained on images and data from 5,000 confirmed coronavirus cases and has been tested in hospitals throughout China. Per a report, at least 100 healthcare facilities are currently employing Alibaba’s AI to detect COVID-19.

Ping An Insurance (Group) Company of China, Ltd (Ping An) aims to address the issue of lack of radiologists by introducing the COVID-19 smart image-reading system. This image-reading system can read the huge volumes of CT scans in epidemic areas.

Ping An Smart Healthcare uses clinical data to train the AI model of the COVID-19 smart image-reading system. The AI analysis engine conducts a comparative analysis of multiple CT scan images of the same patient and measures the changes in lesions. It helps in tracking the development of the disease, evaluation of the treatment and in prognosis of patients. Ultimately it assists doctors to diagnose, triage and evaluate COVID-19 patients swiftly and effectively.

Ping An Smart Healthcare’s COVID-19 smart image-reading system also supports AI image-reading remotely by medical professionals outside the epidemic areas. Since its launch, the smart image-reading system has provided services to more than 1,500 medical institutions. More than 5,000 patients have received smart image-reading services for free.

The more solutions the better. At least when it comes to helping overwhelmed doctors provide better diagnoses and, thus, better outcomes.

MONITORING

  • AI based Temperature monitoring & scanning

In Beijing, China, subway passengers are being screened for symptoms of coronavirus, but not by health authorities. Instead, artificial intelligence is in-charge.

Two Chinese AI giants, Megvii and Baidu, have introduced temperature-scanning. They have implemented scanners to detect body temperature and send alerts to company workers if a person’s body temperature is high enough to constitute a fever.

Megvii’s AI system detects body temperatures for up to 15 people per second and up to 16 feet. It monitors as many as 16 checkpoints in a single station. The system integrates body detection, face detection, and dual sensing via infrared cameras and visible light. The system can accurately detect and flag high body temperature even when people are wearing masks, hats, or covering their faces with other items. Megvii’s system also sends alerts to an on-site staff member.

Baidu, one of the largest search-engine companies in China, screens subway passengers at the Qinghe station with infrared scanners. It also uses a facial-recognition system, taking photographs of passengers’ faces. If the Baidu system detects a body temperature of at least 99-degrees Fahrenheit, it sends an alert to the staff member for another screening. The technology can scan the temperatures of more than 200 people per minute.

  • AI based Social Media Monitoring

An international team is using machine learning to scour through social media posts, news reports, data from official public health channels, and information supplied by doctors for warning signs of the virus across geographies. The program is looking for social media posts that mention specific symptoms, like respiratory problems and fever, from a geographic area where doctors have reported potential cases. Natural language processing is used to parse the text posted on social media, for example, to distinguish between someone discussing the news and someone complaining about how they feel.

The approach has proven capable of spotting a coronavirus needle in a haystack of big data. This technique could help experts learn how the virus behaves. It may be possible to determine the age, gender, and location of those most at risk quicker than using official medical sources.

PREDICTING

Data from hospitals, airports, and other public locations are being used to predict disease spread and risk. Hospitals can also use the data to plan for the impact of an outbreak on their operations.

Kalman Filter

Kalman filter was pioneered by Rudolf Emil Kalman in 1960, originally designed and developed to solve the navigation problem in the Apollo Project. Since then, it has been applied to numerous cases such as guidance, navigation, and control of vehicles, computer vision’s object tracking, trajectory optimization, time series analysis in signal processing, econometrics and more.

Kalman filter is a recursive algorithm which uses time-series measurement over time, containing statistical noise and produce estimations of unknown variables.

IT Infrastructure Managed Services

For the one-day prediction Kalman filter can be used, while for the long-term forecast a linear model is used where its main features are Kalman predictors, infected rate relative to population, time-depended features, and weather history and forecasting.

The one-day Kalman prediction is very accurate and powerful while a longer period prediction is more challenging but provides a future trend. Long term prediction does not guarantee full accuracy but provides a fair estimation following the recent trend. The model should re-run daily to gain better results.

GitHub Link: https://github.com/Rank23/COVID19

ANALYZING

The Center for Systems Science and Engineering at Johns Hopkins University has developed an interactive, web-based dashboard that tracks the status of COVID-19 around the world. The resource provides a visualization of the location and number of confirmed COVID-19 cases, deaths and recoveries for all affected countries.

The primary data source for the tool is DXY, a Chinese platform that aggregates local media and government reports to provide COVID-19 cumulative case totals in near real-time at the province level in China and country level otherwise. Additional data comes from Twitter feeds, online news services and direct communication sent through the dashboard. Johns Hopkins then confirms the case numbers with regional and local health departments. This kind of Data analytics platform plays a pivotal role in addressing the coronavirus outbreak.

All data from the dashboard is also freely available in the following GitHub repository.

GitHub Link: https://bit.ly/2Wmmbp8

Mobile version: https://bit.ly/2WjyK4d

Web version: https://bit.ly/2xLyT6v

Conclusion

One of AI’s core strengths when working on identifying and limiting the effects of virus outbreaks is its incredibly insistent nature. AI systems never tire, can sift through enormous amounts of data, and identify possible correlations and causations that humans can’t.

However, there are limits to AI’s ability to both identify virus outbreaks and predict how they will spread. Perhaps the best-known example comes from the neighboring field of big data analytics. At its launch, Google Flu Trends was heralded as a great leap forward in relation to identifying and estimating the spread of the flu—until it underestimated the 2013 flu season by a whopping 140 percent and was quietly put to rest. Poor data quality was identified as one of the main reasons Google Flu Trends failed. Unreliable or faulty data can wreak havoc on the prediction power of AI.

References:

About the Author:

Bargunan is a Big Data Engineer and a programming enthusiast. His passion is to share his knowledge by writing his experiences about them. He believes “Gaining knowledge is the first step to wisdom and sharing it is the first step to humanity.”

The Crucial Component of Data-driven Organizations

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Sankul Seth

Data is a crucial component for any organization to generate revenue and provide the best-in-class experience for their customers. Various studies have shown that 60% of the organizations fail to implement UI tools, which are heavily dependent on data-driven technologies because organizations spend millions on buying these tools but not investing in the right talent to achieve them. Understanding of data is the first stepping stone for any organization to be data-driven. I implemented various data solutions from inception to implementation, which helped organizations to derive data-driven decisions. After fifteen years of extensive experience across multiple data technologies and platform, I have developed numerous critical data frameworks which have benefited organizations to be data-driven. The first essential pillar is to build a cohesive and robust enterprise data team.

Data Center Consolidation Initiative Services

Data is a driver for any business intelligence, analytics, insights, marketing campaigns, UI applications, tools, and technologies. It’s crucial to understand why and what the business needs before deciding to invest in any data technologies. Today, organizations are leveraging data for executing campaigns and defining customer 360-degree views to provide personalized and OMNI-channel experience using data KPIs. There are unlimited data tools available, and it became difficult to pick the right one, which fits all the requirements for the business and delivers a perfect solution. It all goes back to find the right leader who has deep experience on both sides of the coin (Business and Technology). It’s hard to find such talent but not impossible, and this decides the success or failure of any data implementation projects.

About the Author:

Sankul is the Vice President of the Enterprise Data Team at PSCU. is a value-driven and business-oriented data and IT technology leader with a proven track record for building enterprise applications and data-driven platforms. He believes the current generation and future leaders should be focused and good listeners, as it helps to perceive and deliver solutions.

Heroes of GAVS

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Every day we witness these heroic acts Of GAVSians!

A special shout-out to our GAVSians who go into the hospital (BronxCare Health Services) every day to keep their vital computer systems going. 

Ivan Durbak, CIO, BronxCare – “Every day we witness these heroic acts: one example out of many this week was our own Kishore going into our ICU to move a computer without full PPE (we have a PPE shortage). The GAVS technicians who come into our hospital every day  are, like our doctors and healthcare workers,  the true heroes of our time.”

“I am especially inspired by my GAVS colleagues who are supporting some of the healthcare providers in NYC. The GAVS leaders truly believe that they are integral members of these institutions and it is incumbent upon them to support our Healthcare clients during these trying times. We thank the Doctors, Nurses and Medical Professionals of Bronx Care and we are privileged to be associated with them. We would like to confirm that 100% of our client operations are continuing without any interruptions and 100% of our offshore employees are successfully executing their responsibilities remotely using GAVS ZDesk, and other tools.” – Sumit Ganguli, CEO

“Customer Success is all about being proactive and getting ready to address newer situations. At GAVS, RITE is a key DNA and Empathy to our teams and customers is absolutely at the top. That drives us to do the right things for both our teams and customers. In this endeavor and to ensure that our teams are safe and healthy and are able to seamlessly provide support and service to our customers, we have created a task force to understand, assess and plan for events that would unfold due to this massive viral pandemic. We have created 3 broad pillars as part of the task force – 1st How do we take care of our people – people safety first (ability to shift GAVS and customer assets to their home offices smoothly and provide adequate support to enable them to stay in touch with our customers and drive value),  2nd continuation of services and support to customers (continue with newer mechanisms and tools of collaboration and governance) and 3rd is the adoption of new operating model (potential onboarding and collaborative situations in a hybrid model for the future as well and enabling culture for such adoption and collaboration). With these 3 key facets, the task force prepared a plan and executed it with measurable outcomes at every stage. Clear goals and empowerment to various teams enabled us to execute a seamless transition to the new model. We moved 700 assets over a course of 4 business days and created stock and contingency plans for an additional 50% of the workforce.”- Balaji Uppili, Chief Customer Success Officer