The book highlights a number of software engineering techniques to design and develop systems and applications for digital innovation. It covers the institutional perspective of digital innovation and transformation to create novel products and services. It also highlights institutional arrangements critical for digital transformation
Software Engineering Approaches to Enable Digital Transformation Technologies features contributions reflecting ideas and research in enabling digital transformation technologies through software engineering. To date, multiple, different approaches have been adopted to develop software solutions for a variety of different problems. Of all the available approaches, the main approaches are level-oriented, data flow-oriented, data structure-oriented, and object-oriented design approaches. The other focus of the book is digital transformation, which can be defined as the adoption of digital technology to improve efficiency, value, and innovation
Digitalization is more than just putting additional technological systems and services in place. Rather than improving conventional methods, a true digital transformation initiative includes radically rethinking company structures and procedures. There are four types of digital transformation: business process, business model, domain, and cultural and organizational. Companies are being challenged to develop new business models that consider and harness digitalization. From the standpoint of software engineering, digital transformation alters how software is built.
Current trends include the development of mobile applications, cloud applications, and Internet of Things (IoT) applications. Emerging trends are the development of digital twins, robotics, artificial intelligence, machine learning, augmented reality, and additive manufacturing. This book examines the challenges that arise due to digitization in society and presents plausible solutions that could be applied to counter these challenges and convert them into opportunities. These solutions may further be improvised and worked out for the software companies from the technological perspective, organizational perspective, and management perspective.
1. Precise Prediction of Water Level Using Naïve Bayes Algorithm for
Smart Irrigation in Pomegranate Farm
2. A Brief Review on Lightweight
Practice of Docker Vulnerabilities
3. Deep Learning-Based Serverless Image
Handler using Amazon Web Services
4. Ontology Based Delegation Enforcement in
the Cloud Ecosystem
5. Applicability of Artificial Intelligence for Social
Development in Rural and Urban Sectors
6. Disease Prediction Using Bayes
Theorem
7. Secure Voting System using Blockchain Technology
8. Malware
Analysis: An Experimental Approach
9. Deployment of New Life Cycle Model for
Applications of Web
10. The Future Possibilities of Artificial Intelligence
In Modern Drapes
11. Mobile Application and Communication
12. Emerging and
Growing Technologies in Blockchain Security.
Prof. Sanjay Misra, PhD, is a scientist at the Department of Applied Data Science, Institute of Energy Technology, Halden, Norway. He is also a senior member of the Institute of Electrical and Electronics Engineers (IEEE).
Amit Jain, PhD, MBA, FDP, is vice chancellor, dean of the Faculty of Management Studies, and director of Amity Business School, Amity University, India.
Manju Kaushik, PhD, MCA, MTech CS, MSc, MBA, is a professor, Amity Institute of Information Technology, and the president of the Institutes Innovation Council, Amity University Rajasthan, India.
Prof. Chitresh Banerjee, PhD, MTech CS, MCA, B.Sc., GNIIT, is an associate professor, Amity Institute of Information Technology, and the vice president of the Institutes Innovation Council, Amity University Rajasthan, India. He is also a member of Machine Intelligence Research (MIR) Labs, United States.
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