Top 6 Emerging Digital Transformation Trends to Watch in 2021

by January 1, 2021 0 comments

Emerging Digital Transformation Trends

Recent advances in digital technology have redefined the world and are continuously changing the way people live and work. Technology, including AI, cloud computing, sensors and analytics, etc is expediting progress exponentially. Such digital technologies are creating new profit pools by reinvigorating customer expectations and how companies can address them. As digital transformation provides industry with unparalleled opportunities, here are 6 technologies transforming trends across diverse industries at large.

 

Augmented Reality in Retail/E-commerce

 

What is Augmented Reality?

Augmented Reality (AR) is an enhanced version of the real physical world that is achieved through the use of digital visual elements, sounds, or other sensory stimuli delivery via technology.

 

Use Cases:

Virtual fitting rooms- Customers can visualise themselves in the chosen pair of clothes in front of a mirror/screen and check the colour, design and fit.

Store Navigation– When a customer is looking for a particular product, augmented reality can make the experience smooth. Store navigation directs the consumer to the desired product area.

Product Customisation– An AR-enabled mobile app can act as a salesperson and provide with options relevant to the customers need.

 

Intelligent Edge in Business

 

What is Intelligent Edge?

Intelligent edge refers to the analysis of data and development of solutions at a site where the data is generated. By doing this, intelligent edge reduces latency, costs, and security risks, thus making the associated business more efficient.

 

Use Cases:

Developing an integrated solution– Partners can develop fully integrated solutions at an end-to-end control over execution and quality of service by leveraging intelligent edge.

Safe alternative– As 5G technology is advancing, it is safe to move computing, storage and intelligence to the edge as a viable alternative.

 

Blockchain in Healthcare 

 

What is Blockchain Technology?

Blockchain technology is a decentralised, database management that stores the data in a sequential arrangement, with each transaction made by the user, available to the public. Blockchain ensures transparency amongst the users.

 

Use Cases:

Medical Data and Sharing- Over the years, the healthcare sector has become targeted with cyberattacks, while sharing patients’ information. Blockchain facilitates transparency while transferring patients’ data from one system to another, thus mitigating the risk of cyber malware.

Medical Research – By maintaining historical data of clinical trials, Blockchain lessens result switching, data snooping, unethical reporting, fraud and error in medical research.

 

IoT in Smart Cities

 

What is the Internet of Things?

The Internet of Things refers to gathering and sharing of data amongst the devices that are on the same network. With its robust sensor system, a device can collect data and operate in alignment with other devices.

 

Use cases:

Smart Infrastructure with IoT – IoT enabled sensors, integrated over the smart buildings, will aid in energy-efficient and environment-friendly infrastructure.

Smart Waste Management – By integrating a level sensor over the waste containers, the authorities will get alerted when a threshold of waste gets reached. This will aid in timely waste collection and management.

 

Computer Vision in Archaeology

 

What is Computer vision?

Computer vision refers to the field of computer science that focuses on imitating the complexity of the human vision system enabling computers to recognize and process objects in images and videos.

 

Use Cases:

Imagery Analysis – As computer vision is all about pattern recognition, it understands visual data to given images that have been labelled. It allows for more objective and more controllable classification of archaeological artifacts.

Automatic Object Classification – Computer vision can expedite the classification process of historical artifacts. It can give a broader public access to archaeological knowledge by providing automatic classification systems to non-experts and allowing for new presentation methods for online archaeological collections.

New Typologies Development – Computer vision techniques allow archaeologists to develop new typologies or to gauge old ones. For instance, applying visualization techniques like MDS on the shape analysis of the entire historical glass collection leads to similarity maps. By manually creating clusters in these maps, the archaeologist can easily create a new typology.

 

Data Science in Agriculture

 

What is Data Science?

Data science, an emerging inter-disciplinary field of data analysis, translates raw data into actionable insights. This filed of study comprises a broad array of career opportunities such as Data Scientists, Data Analysts, Data Architect, Machine Learning Engineers and others.

 

Use Cases:

Managing Crop Diseases and Pests – Data scientists help the farmer by providing meaningful information concerning when to apply pesticides and how much to use. This significantly prevents the misuse of pesticides that can have an adverse impact on people, plants and others.

Weather Forecast – The quality of crops relies heavily on the weather. Bad weather can harm the crop’s quality during transportation or storage. Data science experts use tools that identify the patterns and relationships that may otherwise be concealed. They predict weather conditions by using datasets gleaned from farmlands.

Yield Predictions – A poor yield can result in an upsetting season for farmers and the entities depend on the crops. With adequate data collected from farms, data science experts can envisage soil chemical, physical and biological properties, weather, water composition, land type, fertilizer characteristics, and many more that can help improve yield production.

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