Empowering Healthcare: A Comprehensive Tech Solution to Oxygen Crisis Amidst the Pandemic

  • Business
  • Development

Find out how our company managed connectivity and used IoT to develop a technology solution that enabled the Indian Government to solve issues relating to the disconnectivity of oxygen concentrator plants and the lack of real data during COVID-19, which made it crucial to save the lives of those dying from lack of oxygen availability.

About Project
Artiscien provides digital transformation services worldwide. Here is a success story involving a project initiated by the Indian government and executed by a private defence company with our assistance. Artiscien was a cooperative IT partner in the completion of this project.

The brutal second wave of the COVID-19 pandemic exposed India’s critical healthcare infrastructure gaps, particularly in oxygen availability. However, amidst the crisis, a technological innovation emerged as a beacon of hope. This solution, driven by the trifecta of Internet of Things (IoT), Cloud Computing, and Artificial Intelligence (AI), revolutionized oxygen concentrator plant management and saved countless lives.

This innovation helped the Indian Government to rescue thousands of lives by managing the connectivity of oxygen concentrator plants and establishing a centralised control and command centre to provide real-time information relevant to oxygen concentrator plants and their management. The innovation truly helped those common people who were dying because of lack of oxygen availability in their place and no real updates for the same.

Read below and discover how this innovative tech solution helped not only common people but also the Indian government to rescue thousands of lives during the second wave of the pandemic.

Understand the Problem /  Background
Let’s know a bit about the background of the project:

You all know the scenario during the 2nd wave of COVID-19 across the world. As India battles the 2nd wave of the COVID-19 pandemic, the surge of new infections has resulted in an alarming increase in the number of active cases. The situation led to a big spike in demand for oxygen concentrators and plants which can manufacture them. This big demand brought the following major problems:
There were some existing oxygen concentrator plants in some areas but they were unable to connect.
There is no central system through which various oxygen concentrator plants located in long-distance geographical areas get connected and communicate with each other.
It was tough to have a 360 view of the supply and demand of oxygen because of the lack of a centralized control and connectivity system.
Experts were unable to check the purity of the oxygen as there were no quality parameters to assess and test the working of oxygen concentrators.
There was no disaster recovery plan which could support recovery disasters like COVID-19.

These problems caused one big requirement: “Ensurety of at least one hospital in each district should have one oxygen concentration plant.” It was not easy to fulfil this requirement and there were many challenges to fulfil this requirement. In other words, there was a need for a technical solution rather than a generic solution to solve these problems.

After understanding all the problems, Artiscien figured out all the challenges which were about to come while fulfilling that requirement. Let’s understand those challenges:
Design & connect PLCs: It is already clear that there was a need for oxygen concentrator plants but it was challenging to establish a connection between them. For this, designing and connecting PLCs was essential for an affordable cost and short period.
Design a centralized command and control system: The next challenge was designing one centralized command and control system which could connect all oxygen concentrator plants into one place. In other words, there was a need for one centralized dashboard to provide real-time updates such as “How many plants are active and working properly?”, “What is the quality of oxygen in the plants”, etc.?
How to enable preventive and scheduled maintenance of devices and plants: Lack of preventive and scheduled maintenance always creates issues and is unable to provide exact outcomes. It was a challenging task to design a maintenance system through technology and get information like “Are all devices or machines working properly or not”, and “Maintenance has been taking place or not ”.
Report generation: To predict any machine or plant and its working condition, a report is required. Similarly, to understand the quality of concentrated oxygen, a report is required. Now, it was challenging to design one web application and a mobile application to generate such reports. And also get
Notification and escalation: In case of a problem occurring during the oxygen concentration process or other similar cases, it is essential to send a notification to an authorized expert. For us, designing an app or system is another complex task which can automatically generate tickets to solve such problems.

Our Solution: Tech-Powered Lifeline
To overcome the above-discussed challenges, the company leveraged three main technologies including IoT, Cloud Computing, and Artificial Intelligence. The company’s major responsibility was to connect all plants and manage the centralized command and control system from which all plants were connected.

Let’s understand how each technology contributed to solving these challenges:

PLC programming:
A programmable Logic Controller or PLC is a ruggedized computer or industrial computer used for industrial automation. These are controllers which can automate specific processes, machine functions, or production lines. Based on requirements, different PLCs were designed.

The main purpose of using PLCs was to control manufacturing processes such as machines and devices within plants. PLCs’ main job was to receive information from connected sensors or input devices, process the data, and trigger outputs according to pre-programmed parameters. It also monitors and records run-time data such as operating temperature, and machine productivity, and generates alarms if a machine malfunctions. It was also communicating data via web browser and connecting to database and cloud.

(Did we use already designed PLCs) or we designed various PLCs ourselves?)

IoT connectivity
The company leveraged IoT to establish connections and data communication. The major objective of using IoT was to create connected industrial oxygen concentration plants through embedded systems, control systems, wireless sensor networks, and automation.

It is known that IoT collaborate custom-designed technologies to interconnect internet-enabled physical devices and enable communication with each other through a wireless network. Thus, the company programmed IoT devices such as sensors, actuators, machines, and other physical equipment, software, hardware, gateway, and connectivity and created a device layer to transmit data and perform specific tasks through wireless networks within concentration plants.

After designing this layer, the IoT gateway is configured to connect IoT devices to the cloud. Sensors helped to collect data from devices and these data moved through the gateway and processed at the edge. And, finally sent to the cloud.

Since, there was a need for real-time information access and updates, thus, high capacity and low latency, a 4G LTE IoT wireless network was used to enable communication.

IoT protocol, “Internet Protocol (IP)” helps devices to communicate with each other. It also provides surety that information from one device or data collected by the sensor gets read and understood by the gateway.

The IoT platform made it easy to launch this IoT project by providing a single service to manage the whole deployment, devices, and data. This platform includes IoT cloud gateway, device management, APIs, cloud infrastructure, and third-party app integration.

In this way, the company built an IoT platform and system to connect plants with one centralized control and command system.

AI & Machine learning:
Since IoT connected more than 300 plants, IoT systems collected a large amount of real data. To process these data, AI & machine learning have been used.  The core purpose of using these technologies was to analyse these large data and help to find out patterns, take required actions, and make intelligent decisions

AI also helped in preventive and scheduled maintenance of devices and plants by predicting the need for maintenance, downtime from unexpected breakdown of machines, or reducing costs.

An automatic ticket generation system was built to create an automatic ticket in case of a breakdown or repair of machines and define SLA. According to this SLA, the company set up SLA notifications and escalations to fix any problem quickly.

For instance, IoT-enabled oxygen concentrators provided real-time data on oxygen purity levels, pressure, and flow rates. These data further helped decision-makers and healthcare professionals to monitor patients and adjust oxygen therapy accordingly. Remote monitoring and diagnostics allow us to identify and address issues with the devices before they become critical. This thing reduced the need for on-site maintenance, and repair improved device uptime, and reduced costs.

Cloud Computing & Other Technologies:
The company took the benefits of cloud computing to develop IoT-based cloud infrastructure which enables the use of data generated by devices. It was already clear that every day, a large amount of real and diverse data would be fetched and generated. Thus, the integration of IoT with cloud computing resolved the problem of storing, processing and accessing this huge volume of big data. Besides, big data analytics or Business Intelligence (BI) was also responsible for big data management.

It permitted the generation of on-demand reports according to need. Here, mobile and web application development played a great role in designing mobile and web apps for technicians and decision-makers.

In this way, all these technologies, especially IoT, played a vital role in achieving success in this project by converting huge data into insights and driving cost-effective tech solutions.

Nation-wide Connectivity: Achieved success in connecting more than 300+ oxygen concentration plants spread over different geographical areas which are thousands of km away from each other with one centralized command and control system across India. This means connected oxygen concentration plants from North to South and East to West India!
Real-time Dashboard: Built one real-time centralized dashboard to provide real updates relevant to any oxygen concentration plant during the Covid 2nd phase.
On-demand Reports: Achieved success in creating and generating 100+ reports for analysis and making instant decisions using IoT, Cloud, and Big data.
User-friendly mobile & web application: Created one mobile application for technicians to manage all devices at the right time. Also designed one web application to see real-time and offline reports.
Preventive and scheduled maintenance of devices: AI played a great role in designing preventive and scheduled maintenance systems to maintain any device.
Notification & Escalation: The automatic ticket generation system helped to notify, trigger devices, identify bugs and fix any problem or escalate in other cases.

End user benefits:
Innovation, collaboration, and unwavering determination helped us bring hope back to India. Contact Artiscien to optimize your business.

In summary
Challenge: How to connect 300+ oxygen concentration plants and establish communication among them to one centralized command and control centre with a dashboard to get real data.
Solution: Connected +300 plan with one data centralized command and control centre and built a dashboard to generate real-time data. The centralized dashboard helped to provide real updates on time.
Approach: Technologies have been used to connect plants and exchange information.
Result: Achieved success in connecting more than 300+ oxygen concentration plants located in long-distance geographical places with one centralized centre which was able to generate and process real-time data.

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