Microbial Data Intelligence and Computational Techniques for Sustainable Computing / edited by Aditya Khamparia, Babita Pandey, Devendra Kumar Pandey, Deepak Gupta.

Format:

Book

Contributor:

Khamparia, Aditya, editor.

Series:

Microorganisms for Sustainability, 2512-1898 ; 47

Language:

English

Subjects (All):

Microbiology.

Industrial microbiology.

Microbiology--Technique.

Bioinformatics.

Industrial Microbiology.

Microbiology Techniques.

Local Subjects:

Microbiology.

Industrial Microbiology.

Microbiology Techniques.

Bioinformatics.

Physical Description:

1 online resource (398 pages)

Edition:

1st ed. 2024.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2024.

Summary:

This book offers information on intelligent and computational techniques for microbial data associated with plant microbes, human microbes etc. The main focus of this book is to provide an insight on building smart sustainable solutions for microbial technology using intelligent computational techniques. Microbes are ubiquitous in nature, and their interactions among each other are important for colonizing diverse habitats. The core idea of sustainable computing is to deploy algorithms, models, policies and protocols to improve energy efficiency and management of resources, enhancing ecological balance, biological sustenance and other services on societal contexts. Chapters in this book explore the conventional methods as well as the most recently recognized high-throughput technologies which are important for productive agroecosystems to feed the growing global population. This book is of interest to teachers, researchers, microbiologist, computer bioinformatics scientists, plant and environmental scientist, and those interested in environment stewardship around the world. The book also serves as an advanced textbook material for undergraduate and graduate students of computer science, biomedicine, agriculture, human science, forestry, ecology, soil science, and environmental sciences and policy makers.

Contents:

1. The Contribution of Artificial Intelligence to Drug Discovery: Current Progress and Prospects for the Future

2. Prediction of Plant disease using Artificial Intelligence

3. Computer Vision Based Remote Care of Microbiological Data Analysis

4. A Comparative Study of Various Machine Learning (ML) Approaches for Fake News Detection in Web based Applications

5. Analytics and Decision-Making Model Using ML For IoT Based Greenhouse Precision Management in Agriculture

6. Distil-BERT based Text Classification for Automated Diagnosis of Mental Health Conditions

7. An optimized hybrid ARIMA-LSTM model for time series forecasting of Agriculture production in INDIA

8. An Exploratory Analysis of Machine Intelligence Enabled Plant Diseases Assessment

9. Synergizing Smart Farming and Human Bioinformatics through IoT and Sensor Devices

10. Deep learning assisted techniques for detection & prediction of colorectal cancer from medical images and microbial modality

11. IoT Enabled Smart farming and human bioinformatics

12. Smart farming and human bioinformatics system based on Context aware computing systems

13. Plant Diseases Diagnosis with Artificial Intelligence (AI)

14. Analyzing the Frontier of AI-Based Plant Disease Detection: Insights and Perspectives

15. Fuzzy and Data Mining Methods for Enhancing Plant Productivity and Sustainability

16. Plant Disease Diagnosis with Artificial Intelligence (AI)

17. Sustainable AI driven Applications for Plant Care and Treatment

18. Use Cases and Future Aspects of Intelligent Techniques in Microbe Data Analysis

19. Early Crop Disease Identification Using Multi-Fork Tree Networks and Microbial Data Intelligence

20. Guarding Maize: Vigilance Against Pathogens Early Identification, Detection and Prevention

21. Comprehensive Analysis of Deep Learning Models for Plant Disease Prediction

22. Enhancing Single-Cell Trajectory Inference and Microbial Data Intelligence

23. AI assisted methods for protein structure prediction and analysis.

Notes:

Includes bibliographical references.

ISBN:

981-9996-21-X