Understanding the perspective of Digital Twins

The need for digital twins was foreseen way back in 90’s when we started using computers for automation. In the past two decades our society and organizations have gone to great lengths in making hyper automation possible and we live in a gadgets world where every it connected and have some part of it managed through digital technology. We have actually started using Digital Twins meaningfully only in the past 5 to 7 years.

Digital Twins, when you hear these words for the first time, the first thing that you think is, it must be some sort of digital replica of physical things. You are half way there in understanding Digital Twins. 

Digital Twin is an exact virtual (digital) replica of physical product, object, system, process and even human beings to some extent. Digital twins is used for simulation, prototyping, testing and maintenance as well as for investigations of cause and effects for any major issues and risks we face in products, objects, systems, processes etc. 

Digital Twins are of three broad types based on their usage needs,

1.     Digital Twin Prototype (DTP) – As the name suggests this is not a real digital twin but a prototype and generally used for all types of digital prototyping giving a feel of the product, object, system or process.

2.     Digital Twin Instance (DTI) – DTI is an actual Digital Twin (virtual instance) of a  product, object, system or process. DTI is used for carrying our multiple scenario simulations and testing on the virtual instance.

3.     Digital Twin Aggregate (DTA) – DTA is combination of multiple instances (samples) of the same product, object, system or process. This is used to carry out detailed simulations and tests on aggregated instances. It is very useful for validating how the hundreds of thousands of instances of digital twins could work and what challenges and issues we might face as we ramp up or ramp down the instances, upgrades, maintenance and support. 

Digital Twins are used in 3D modelling, architecting, construction, manufacturing, retail, healthcare, automotives, aviation, shipping, smart cities and many more industries. Here are some major examples,

1.     Retail – Digital Twins are used in the retail industry to model consumers and study their behaviors to enhance user experience.

2.     Healthcare – Digital Twins are used in the healthcare industry for multiple areas,

a.     For products simulations and tests

b.     For patient simulations and tests

c.     For Hospitals and Clinics process simulations

d.     For staff trainings using digital twins

3.     Automotives – Digital Twins are used in the automotive industry for parts simulations as well as product simulations and testing

4.     Manufacturing – Digital Twins can be used to simulate how industry and manufacturing lines can perform in various scenarios.

5.     Architecting – Digital Twins can be used for 3D modeling and architecting simulations and tests.

6.     Aviation and Shipping – Digital Twins can be used for aircraft, spacecraft and ships simulations and testing

7.     Construction – Digital Twins can be used for major construction modelling and simulation testing.

8.     Smart Cities – Countries and Governments can use Digital twins for simulating smart cities and how they can meet their growth and sustainability goals.

Microsoft Azure Digital Twins Overview for Smart Cities

The need for digital twins is clear from above examples. Please also check above picture of Microsoft Azure Digital Twin Overview of a Smart City. Digital twins help in ensuring before we launch the new product, object, system or process as well as before we upgrade we do a thorough virtual simulation and testing to understand the quality, impact, issues and risks. The outcome helps in addressing all the areas sufficiently before launching. Here are some real examples specifying why we need digital twins,

1.     Imagine the impact for an airline company of recalling its aeroplanes for any parts defects post product launch.

2.     Imagine the impact of healthcare device recall post launch and how much it will impact organization’s brand and finances.

3.     Imagine an automotive company recalling its cars to address defective part which did not get sufficiently tested.

4.     Imagine a space rockets company having its rocket failure due to insufficient simulation tests.

5.     Imagine a trading company launching a defective trading app and how much of impact it can create for its customers.

6.     Imagine a construction company building a construction project without full simulation and tests.

These are only few examples why we need digital twins to improve simulation and testing with virtual instances. There are many more examples across all industries and sectors.

Here is a quick understanding on how the digital twins are setup and how do they function,

1.     Digital twins are setup and created as virtual instance(s) that get(s) data feed from the physical instance(s). 

2.     The data is fed using system interfaces or data loads for specific scenarios simulations and tests. 

3.     The results are collected and recorded from different parts of the respective product, object, process or system.

4.     The results are collated and visualisations are created for concluding on insights.

5.     Insights lead to actions and possibly some more simulations and tests until the respective product, object, process or system meets all criteria.

Digital Twins can be created using company proprietary or market standard platforms. Microsoft, Nvidia, IBM, Siemens, Cisco, Oracle, Ansys, General Electric and many other companies offer Digital Twin platforms, solutions and services.

Digital Twins are an essential part of Industry 4.0 and Digital Transformation for organizations’ digital value chain. Digital twins are also closely attached and work in conjunction with the IoT (Internet of Things) and IIoT (Industrial Internet of Things) ecosystems. Digital Twins can also be understood as Metaverse made for the reverse engineering of investigations and simulations.

Digital Twins are very useful for organizations, industries, sectors and countries. As it costs to have a Digital Twin, it is important to not apply Digital Twins for every product, object, process and system. Digital Twins should be applied to only mission critical, high impact and high risk products, objects, processes and systems.

Digital Twin are a necessity for organizations as their products and value chain becomes digital through digital transformation and digital business models. In near future more easy to use platforms, solutions and services will emerge that will make using Digital Twins simpler and faster for all.


The What, How and Why of Internet of Things (IoT)

The Internet of Things (IoT) is a term that came in real use more than a decade ago. It arrived when our mobile devices became more powerful and gained ability to connect to internet and communicate information. IoT opened a new world of connected eco systems for tracking, monitoring and reporting on all possible aspects of our lives.

IoT is the ability of mobile devices, scanners, sensors and tokens to connect to internet or to an internet enabled device to share useful information collected by the device, scanner, sensor and token. The information can be then be collated and stored on a cloud hosted systems that can then analyze the data and share insights and actions.

The IoT ecosystem consists of many devices connected to the IoT Hubs which are connected to the IoT Cloud Platform that collects and analyzes data which is accessed by the organization using their devices to gather insights and make decisions. The IoT ecosystem can be briefly described as follows,

Internet of Things

1.  IoT Devices – IoT devices consists of sensors, trackers, scanners either on their own or as part of products like smart band, smart watch, smart cars, smart phones, smart thermometers, smart weighing machines and many more. The devices are built in to communicate with IoT Hubs using protocols like IPv6, LoRaWan, ZigBee etc.

2.  IoT Hub – Each IoT device has ability to connect to the nearest possibly IoT Hub. The IoT Hub has the ability to receive and translate the data from IoT devices. It translates and tags it properly as well as encrypts it to send it to IoT Cloud Platform.

3.  IoT Cloud Platform – The cloud platform is a large storage space with suite of applications to store, analyze and interpret data patterns. It prepares the insights and visualizations for the organization to access the data and results to make effective decisions.

4.  User Devices – The data and insights stored in the IoT Cloud platform can be accessed by respective authorized users using mobile, tablet or PCs to make decisions and take necessary actions as well as do required communications.

There are many IoT Communication Standards as different manufactures and industries need different types and standards are not fully underpinned by one global entity. Here are some of the known standards that are generally used by IoT devices for communications.

1.  Long Range Wide Area Network (LoRaWAN) is a protocol for wide area networks (WANs) designed to support big size networks. It is generally used for large scale environments like smart cities with ability to connect and enable communications for millions of low-power devices.

2.  Low-Power Wireless Personal Area Networks (6LoWPAN IPv6) – It is an open standard that enables low-power radio frequency to communicate to the internet, includes Bluetooth Low Energy (BLE) and Z-Wave used for home automation.

3.  ZigBee – It is also a low-power, low-data rate wireless network used mainly in industrial settings.

4.  LiteOS – It is an operating system used for wireless sensor networks. LiteOS can be used with  smartphones, smart watch, smart bands, smart cars, smart homes and intelligent industrial.

IoT operates in the cloud (internet) so it needs a robust architecture platform and framework. The world known cloud providers have also their own cloud-based platform and framework for organizations to effectively operate IoT ecosystem. Here are some well-known examples of IoT platforms and frameworks.

1.  Brillo / Weave by Google – Google has developed Brillo and Weave platform for rapid implementation of IoT applications. Brillo is Android OS based platform that helps develop apps for managing and tracking embedded low powered devices. Weave is messaging protocol used between the IoT device and google cloud.

2.  AWS (Amazon Web Services) IoT platform – It offers services that enable interaction with IoT devices and enables ability to receive data from IoT devices. The platform also doubles up in analyzing the data and sharing visualization as well as insights for decision making.

3.  Azure IoT platform by Microsoft – The Azure IoT platform offers services that allow interaction with IoT devices as well as ability to receive data from IoT devices. The platform also offers data analysis, visualizations and insights from the collected data.

4.  HomeKit for iOS by Apple – Apple devices have several sensors as well as products like Air Tag, Smart Watch and Air Pods have several IoT services. The HomeKit is proprietary platform that can be used for iOS apps development to interact and receive data from Apple devices and sensors.

Here are some examples for you to better understand what IoT can do and how it helps in efficiency, effectiveness and continuity of services, 

1.  A sensor in the rental printer can communicate cartridge usage status and auto dispatch refill/replacement cartridge in time to ensure continuity of the printing services.

2.  A sensor in the smart watch can monitor and detect your health and predict your health conditions improvements over a period of weeks and months.

3.  A sensor in the smart watch can monitor and detect your fall and automatically call the emergency services to support you.

4.  A sensor in the logistics pallet can track and share the exact location of the pallet throughout its journey from warehouse to delivery. It can also help track areas where it takes longer than usual for clearance and movement of stocks.

5.  A sensor in the car can track your driving speed and alert you when you are crossing a certain speed limit.

6.  A sensor in the mobile phone can monitor battery health and suggest when it’s time to charge and or change batteries.

7.  Smart sensors in the manufacturing production line can track the performance and effectiveness of the production line and report alerts when its either too fast or too slow.

8.  Smart sensors in the retail shop can track how many customers come to the product booth, how many spend time trying the product to check the effectiveness of instore excellence and promotions.

9.  The sensors in the aircon can alert service provider for gas top or air con cleaning based on its usage.

10.  The sensors in the hospital MRIs can track and auto order parts replacement in advance to avoid any downtime of MRIs and impact to patients.

11.  The smart patch sensors put on patients’ body can track and monitor their heart rate, oxygen level, blood pressure and diabetes. The data can be then collated and accessible for the patient and care givers for review and actions.

Above list was just a few examples that you can relate easily. The IoT examples and usage is far vaster and there are many more examples. We use IoT across most of our home appliances, entertainment devices and health devices.

IoT has many benefits for organization. Benefits range from automation of repetitive tasks to productivity increase, from insights to costs savings and faster fact-based decision making. Here is a brief overview of key benefits from IoT,

1.  Automation of tracking and monitoring activities without any room for human errors.

2.  Time savings and productivity gain

3.  Cost savings and 7×24 monitoring, tracking and reporting

4.  Faster, Accurate and Facts driven insights and decision making

5.  Improved quality and customer experience

IoT also has some areas to be well taken care, as anything that is on internet is prone to possible cyberattacks and hacking. Here are a few areas to look out for,

1.  The data from IoT devices if not well encrypted can be hacked and even manipulated by hackers. 

2.  The IoT devices can be hacked or virus implanted which can make them malfunction and report bad data.

3.  IoT devices and sensors must be managed for effectiveness as over a period of years the organization could have thousands of such devices all over their customer base and its very difficult to track and manage all of them with speed.

4.  As the amount of data increases its important for organizations to have a policy on how to archive the data periodically to avoid systems from slowing down and increase in costs due to increase storage and computing power.

5.  Regular firmware upgrades and security upgrades for IoT devices and systems to avoid having any security holes making them vulnerable for cyber-attacks.

6.  Another important area for IoT is to ensure full adherence of Data Privacy and regulatory compliance especially for personal, healthcare and confidential data.

IoT has slowly and silently slipped in our daily lives. We all use it every single day and benefit from it to make our lives better. The usage is wide and almost every industry and every person uses IoT in one or the other form. The most common form is smart phone, smart watch and smart bands we use daily.

IoT devices and ecosystems will continue to remain and become even more smarter in the coming years to make our lives super effective and highly efficient.