Optimized Computational Intelligence Driven Decision-Making
Description
This book covers a wide range of advanced techniques and approaches for designing and implementing computationally intelligent methods in different application domains which is of great use to not only researchers but also academicians and industry experts.
Optimized Computational Intelligence (OCI) is a new, cutting-edge, and multidisciplinary research area that tackles the fundamental problems shared by modern informatics, biologically-inspired computation, software engineering, AI, cybernetics, cognitive science, medical science, systems science, philosophy, linguistics, economics, management science, and life sciences. OCI aims to apply modern computationally intelligent methods to generate optimum outcomes in various application domains. This book presents the latest technologies-driven material to explore optimized various computational intelligence domains.
- includes real-life case studies highlighting different advanced technologies in computational intelligence;
- provides a unique compendium of current and emerging hybrid intelligence paradigms for advanced informatics;
- reflects the diversity, complexity, and depth and breadth of this critical bio-inspired domain;
- offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in dealing with cognitive informatics challenges;
- presents a variety of intelligent and optimized techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional data analytics research in intelligent decision-making system dynamics;
- includes architectural models and applications-based augmented solutions for optimized computational intelligence.
Audience
The book will interest a range of engineers and researchers in information technology, computer science, and artificial intelligence working in the interdisciplinary field of computational intelligence.
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Persons
Hrudaya Kumar Tripathy, PhD, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, He has more than 20 years of teaching experience and his research interests include neural networks, pattern recognition, software engineering, machine learning, and big data. He has published several books and research papers in various journals and conferences. Tripathy received the 2013 Young IT Professional Award from the Computer Society of India.
Sushruta Mishra, PhD, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, Odisha, India. He obtained his doctorate in 2017 and his research interests include image processing, machine learning, the Internet of Things, and cognitive computing. He has published 130+ research articles in international journals and conferences.
Minakhi Rout, PhD, is an associate professor in the School of Computer Engineering, KIIT Deemed to be University, Odisha, India. She obtained her PhD in 2015 and her research interests focus on computational finance, data mining, and machine learning. Rout has published 50+ research papers in international journals and conferences.
S. Balamurugan, PhD, is the Director of Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India. He is also Director of the Albert Einstein Engineering and Research Labs (AEER Labs), as well as Vice-Chairman, Renewable Energy Society of India (RESI), India. He has published 45 books, 200+ international journals/ conferences, and 35 patents.
Samaresh Mishra, PhD, is the director of student affairs at KIIT Deemed to be University. He obtained a PhD in computer science from Utkal University. His research areas focus on software testing, machine learning, and cloud computing. He has published 30+ academic papers.
Content
Preface xv
1 Emergence of Advanced Computational Intelligence Coupled with Smart Environment 1
Risha Rani and Tirtha Deb
1.1 Introduction 2
1.2 Background Works 3
1.3 Integrated Smart Environment 4
1.4 Proposed Models for Smart Intelligent Environment 5
1.5 IoT Architecture 16
1.6 Smart Environment and Advanced Computational Intelligence 23
1.7 Advanced Computational Intelligences: Possible Uses in Smart Environment 24
1.8 Conclusion 26
2 Machine Learning-Enabled Integrated Information Platform for Educational Universities 29
Sai Smurti Sahu, Rishav Kumar, Soumya Sahoo, Balwant Kumar and Padmabati Mohanta
2.1 Introduction 30
2.2 Cloud-Based Web Application for University 30
2.3 Integrated Information Platform of Indian Universities Using Machine Learning 36
2.4 Applications Used to Designed This Web Platform 37
2.5 Analysis Result 38
3 False Data Injection Attack Detection Using Machine Learning in Industrial Internet of Things 49
Hafizunisa, Prerna Rai and Damini Sinha
3.1 Introduction 50
3.2 Literature Review 54
3.3 Technical Methodology 56
3.4 Proposed Model for Detecting False Data and its Correction 59
3.5 Complexity Analysis of Proposed Model 63
3.6 Advantages of the Model 64
3.7 Future Scope and Limitations of the Proposed Model 65
3.8 Conclusion 65
4 Fake News Detection: Restricting Spreading of Misinformation Using Machine Learning 69
Shubham Choudhary and Pratyush Mishra
4.1 Introduction 70
4.2 Scope of False News Detection 73
4.3 Main Highlights of the Analysis 73
4.4 A Novel Model for False News Detection 76
4.5 Literature Review 78
4.6 Results and Analysis 80
4.7 Conclusion 81
5 Adaptability, Flexibility, and Accessibility Through Telemedicine 85
Dipti Verma, Somyajyoti Talukdar and Kumari Alankrita Sharma
5.1 Introduction 86
5.2 Related Works 89
5.3 Proposed Model for Remote Health Monitoring System 93
5.3.1 Microcontroller and Sensor 95
5.4 Benefits of the Proposed Model 96
5.5 Constraints of the Proposed Model 98
5.6 Conclusion 101
5.7 Future Works 102
6 Crop Prediction by Implementing Machine Learning in an IoT-Based System 107
Vivian Rawade and Shubham Sahoo
6.1 Introduction 108
6.2 Literature Review 110
6.3 Proposed Model for Crop Prediction 112
6.4 Results and Analysis 123
6.5 Challenges Faced 125
6.6 Advantages of the Proposed Model 127
6.7 Disadvantages of the Proposed Model 127
6.8 Conclusion 128
7 Relevance of Smart Management of Road Traffic System Using Advanced Intelligence 131
Koustab Chowdhury and Rishabh Kapoor
7.1 Introduction 132
7.2 Related Works 135
7.3 Proposed Model of Traffic Management System 139
7.4 Role of AI in Traffic Management 146
7.5 Conclusion and Future Works 148
8 Visualization of Textual Corpora Using Social Network Analysis 151
Indu Rodda and Durga Bhavani S.
8.1 Introduction 152
8.2 Related Literature 154
8.3 Proposed Method 156
8.4 Implementation and Results 163
8.5 Conclusion and Future Work 169
9 Autonomous Intelligent Vehicles: Impact, Current Market, Future Trends, Challenges, and Limitations 173
Kamalanathan Shanmugam, Muhammad Ehsan Rana and Felix Ting Yu Hong
9.1 Introduction 174
9.2 The Global Impact of the AV Industry 176
9.3 Role of Machine Learning in Autonomous Vehicles 177
9.4 Significance of the AV Industry in Various Sectors 179
9.5 Current Market and Future Trends in AV Industry 184
9.6 Challenges and Limitations 189
9.7 Conclusion 192
10 Role of Smart and Predictive Healthcare in Modern Society 195
Muhammad Ehsan Rana and Manoj Jayabalan
10.1 Introduction 196
10.2 Healthcare System 197
10.3 Role of Predictive Analytics in Healthcare 198
10.4 Application of IoT in Healthcare 199
10.5 IoT Based Healthcare Management Framework 200
10.6 Future Recommendations for Research 210
10.7 Conclusion 211
11 An Analytical Study on Depression Detection Using Machine Learning 215
Angelia Melani Adrian and Junaidy Budi Sanger
11.1 Introduction 216
11.2 Literature Survey 217
11.3 Proposed System 220
11.4 Challenges of Machine Learning in Depression Detection 225
11.5 Conclusion and Future Work 226
12 Revolutionizing Healthcare: Empowering Faster Treatment with IoT-Powered Smart Healthcare 229
Prerna Kumari, Rupali Agarwal and Shruti Kumari
12.1 Introduction 230
12.2 Scope/Motivation 233
12.3 Literature Survey 234
12.4 Smart Technology 235
12.5 Methods and Materials 236
12.6 Result 245
12.7 Conclusion 248
13 Machine Learning Algorithms for Initial Diagnosis of Parkinson's Disease 251
Udayan Das, Manish Jena and Manish Roy
13.1 Overview of Parkinson's Disease 251
13.2 Scope 254
13.3 Related Works 255
13.4 Comparative Analysis of Parkinson's Disease 260
13.5 Pros and Cons Using ML Algorithms 267
13.6 Conclusion and Future Works 271
13.7 Bibliography 271
14 Towards a Sustainable Future: Harnessing the Power of Computational Intelligence to Track Climate Change 275
Satyam Sinha, Shreyash Kumar Agnihotri and Oshmita Sarkar
14.1 Introduction 276
14.2 Artificial Intelligence and Climate Change Adaptation 277
14.3 Related Works 278
14.4 Comparative Analysis of Technological Frameworks to Handle Climate Crisis 280
14.5 Future Scope of Climatic Crisis Handling with AI 299
14.6 Conclusion 300
15 Impact of Computational Intelligence and Modeling in Tackling Weather Fluctuation 305
Rohan Karn, Aniket Rouniyar, Ranjit Kumar Das and Amit Gupta
15.1 Introduction 306
15.2 Objective 308
15.3 Causes of Climate Crisis 309
15.4 Significance of AI and Modeling on Climate Crisis 311
15.5 Plastic Waste Detection Model 319
15.6 Forest Fire Prediction Models Using AI 325
15.7 Results 329
15.8 Conclusion 331
References 332
Index 335
1
Emergence of Advanced Computational Intelligence Coupled with Smart Environment
Risha Rani* and Tirtha Deb
Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India
Abstract
In this paper we have tried to work out various models which may elevate the lifestyle of us humans by using the technology of present day IoT system concept making it possible to make things or our daily requirement smart or very easily available. As for the models, we have thoroughly studied and discussed how we would build smart homes using various sub disciplines such as building garbage monitoring systems and a system in which we detect any accident. We also went through the whole idea of the present day healthcare system and we built a model for a smart healthcare system and how we can build a weather monitoring system, an Air Pollution monitoring system. Considering the extra need for the noise surrounding the environment, we have proposed a model for Noise Pollution monitoring system. We have proposed a forest fire detection system model. We also have tried to bring the knowledge of advanced computational intelligence and artificial intelligence to our work as we believe the huge significance of advanced computational intelligence and AI inside the development of smart green terrain is a manner to attain clever green frugality.
Keywords: Advanced computational intelligence, scalability, security, connectivity, analyzing and integration
1.1 Introduction
The things which we can hardly imagine are encouraged and supported by new opportunities that the IoTs is reinventing. The Internet of Things is changing our physical world to grow. Through the Internet of Things, the devices that are connected through the internet are designed to become specific, customized, and intelligent to fully fill our unique and day-to-day necessity and requirements. The word smart stands for making Specific, Measurable, Achievable, Relevant and Time-bound objects and the word environment means the surroundings. A smart environment is therefore said to be the ability to acquire knowledge and apply it to modify the needs of its residents to improve their occurrence with that environment. By using various wireless technologies we can enhance the functional capabilities of smart devices. According to reports from Cisco, 50 billion objects and devices will be connected to the Internet 2020. More than 99% of things available in the world today still remain unconnected. According to a Navigant research report, the number of smart meters installed worldwide will increase to 1.1 billion by 2023. [3] Automotive News reports that worldwide the number of Internet-connected cars will increase from 23 million in 2013 to 152 million in 2024. [5] The significant growth such as forecasting shows that the Internet of Things will become a modern society to conceive a concept of a smart environment. For the integration of IoT devices along with the smart environments, several research efforts have been made with the smart environments. The possibilities of smart objects from the combination of IoT with a smart environment are expanded by allowing remote locations of the environment to be monitored by the users. Primarily based on the software requirements, IoT can be included into various smart environments. Work on intelligent IoT-based environments can generally be divided into the areas: smart cities, smart houses, and smart health. An IoT-based system consists of objects, sensor devices, and a computing and processing unit that can be located in the cloud, a decision-making and action-invoking system. IoT things and devices play a vital role in interaction and communication through data exchange. They respond to actual events in the physical world and also have the effect of triggering processes that trigger various actions and services with or without human intervention. With the enabling current era technologies like advanced computational intelligence, the world is becoming a supremely computerized environment. These enabling technologies are planned for a smart environment focusing on restful life to live in. The digital transformations experts collaborating with the application tests providers lead in the progressed conclusion of the new innovative automation and the Internet of Things. The world in the near future will utilize the knowledge of such specialists for the remodeling of the various cities. The smart environment is characterized by complex systems which require balance between transparency and context awareness. The architecture of such a system responds to the demand space and the incorporation of modular and the design of such architecture are flexible and responsible for the right time production of appropriate services.
Main contribution of the paper:
- How energy and resource management techniques are building up the nation and how more swiftly it can be utilized
- Human computer interaction and building more sophisticated software and algorithms for a smart environment
- Predictive maintenance of the society with the proper system using new technologies
1.2 Background Works
In 2017, Kanishka Majumdar Devices for Integrated Circuit (DevIC), 23-24 March 2017, Kalyani, India. "Development Board", has exact attributes like the microcontrollers in the trade but has some additional features i.e., twice the figures of input and output pins adaptable with Arduino IDE also it is very cost efficient. [1] Soil & Surrounding Testing Module by K. P. Keyur and M. P. Sunil, "Internet of Things-IOT". A farmer can easily be benefited by this model as it is an automated analysis producer of soil moisture, pH, temperature, humidity, etc. It can advise regarding the sprout growth and the amount of further fertilizers needed. LCD screens will be of great use here. Sensors like moisture sensor, pH sensors, humidity sensors, etc., are used. [12] Water Pump ON/OFF via Phone Call by M. Fahim and A. Sillitti, "Anomaly detection, analysis and prediction techniques in IoT environment: A systematic literature review," IEEE Access. It provides an important feature of turning the water pump on or off by using a mere phone call option. It reduces a great deal of labor. [13] Solar Tracking System (Renewable Power Supply) by K. P. Keyur and M. P. Sunil, "Internet of Things-IOT". Solar tracker is built on the idea that solar can provide an alternative of renewable energy fit for the respective farmland. It acts as an automatic single axis solar tracker. Sensors such as the LDR are used here. [6] Electronic Scarecrow by H. Haddad Pajouh, A. Dehghantanha, R. Khayami, and K.-K.-R. Choo. This model basically acts as a scarecrow which can be used to keep the harmful pests off the land. Sensors such as PIRs are being used here [11].
1.3 Integrated Smart Environment
The Internet of Things (IoT) is coming with new technologies to improve human capabilities in this modern world. These means or new technologies promise a high quality of life and professional efficiency; however, with each new advancement in IoT synthesis and human augmentation technologies coming, the challenges of the IoT go far beyond that. The integrated intelligent environment is designed with various applications such as intelligent home systems, intelligent health care, intelligent transportation, intelligent agricultural systems, intelligent electronic management system, intelligent weather monitoring system, intelligent education system, etc. IoT objects and things are connected with RFID tags and sensors that are already in various business applications of the smart environment. RFID tags that utilize intelligent barcodes to identify any item use high-frequency technology in which radio waves transmit data from the tag to a reader that acts as a translator to a computer program. In Figure 1.1, the data of an integrated smart environment are stored in cloud based applications consisting of sensors and connecting IoT devices. It makes it much easier to send and analyze the given data and predict outcomes [8].
Figure 1.1 Integrated smart environment using cloud based application.
1.4 Proposed Models for Smart Intelligent Environment
Figure 1.2 denotes the sensors enabled smart environment for smart cities and homes along with smart healthcare service.
1.4.1 Smart Cities
Smart cities are technologically upgraded urban areas which use smart things, sensors, and electronic methods to collect various data and make life easier. The various functions performed by smart things can be traffic management, multi-city connectivity, pollution control, and smart lighting. The main purpose of smart cities is to make things easier and make us look at things with a new perspective. The Internet of Things makes an impact on various things such as every daily reliable life activity and also to any human's complex emotions. The Internet of things makes benefits for each day to us and the environment. Smart city can device itself as an assistant for anyone's daily schedule telling him/her to get up, make coffee or have dinner and go up to remind the person for dinner. It can detect the health condition if there is a problem or any underlying disease.
Figure 1.2 Smart environment based IoT system in smart cities, smart homes, and smart healthcare.
