A Comprehensive Survey on Societal Applications of Data Analytics as a way Forward
DOI:
https://doi.org/10.63503/j.ijssic.2024.10Keywords:
Data Analytics, Machine Learning, Social Application, Governmental Application, Agriculture and Environmental ApplicationAbstract
Data represents a grouping of facts that have a defined size and value. It is processed into understandable information, logically correct, helpful for any operation to carry out, and something new with the help of the knowledge discovery process. The procedure to investigate, filter, extract, reshape, and visualize data to spot the masked knowledge and facts, data analysis is used. Data analysis has integrated with numerous areas such as the finance and commerce industry, health industry, marketing industry, governance, academics, and a bunch of other industries. And among these applications, most are affiliated with profit-intended industries as compared to societal benefit-cause industries. Therefore, this work is a detailed survey of recent papers which are published between 2017 to 2024 on various societal benefit causes applications affiliated to different domains. To the best of the authors' knowledge, the proportion of societal benefits causes applications reported are lower in numbers if compared with others. Supplementarily, an extensive study for societal applications where data analytics is applied remains uninvestigated. This paper presents a schematic literature survey of societal domains where data analytics is applied. From the literature, it can be said that blending data analytic technologies into the societal domains can help us in numerous matters. In this study, we also proposed a model to analyze the barriers and facilitators related to various societal applications
References
Lioutas, Evagelos D., and Chrysanthi Charatsari. “Big data in agriculture: Does the new oil lead to sustainability?”. Geoforum 109, pp 1-3. 2020
Ang, Kenneth Liminn, and Jasmine Kah Phooi Seng. “Big Data and Machine Learning with Hyperspectral Information in Agriculture.” IEEE Access. 2021
Su, Yan, and Xianping Wang. “Innovation of Agricultural Economic Management in the Process of Constructing Smart Agriculture by Big Data.” Sustainable Computing: Informatics and Systems. pp. 100579. 2021
Kamilaris, Andreas, Andreas Kartakoullis, and Francesc X. Prenafeta-Boldú. “A review on the practice of big data analysis in agriculture.” Computers and Electronics in Agriculture 143, pp. 23-37. 2017
Shu, X., & Ye, Y. “Knowledge Discovery: Methods from data mining and machine learning.” Social Science Research, 110, 102817. 2023
Tsui, K. L., Chen, V., Jiang, W., Yang, F., & Kan, C. “Data mining methods and applications.” In Springer handbook of engineering statistics (pp. 797-816). London: Springer London. 2023
Katal, A., Wazid, M., & Goudar, R. H. “Big data: issues, challenges, tools and good practices.” In 2013 Sixth international conference on contemporary computing (IC3) (pp. 404-409). IEEE. 2013
Gandomi, A., & Haider, M. “Beyond the hype: Big data concepts, methods, and analytics.” International journal of information management, 35(2), 137-144. 2015
Janiesch, C., Zschech, P., & Heinrich, K. “Machine learning and deep learning.” Electronic Markets, 31(3), 685-695. 2021
Hashimi, H., Hafez, A., & Mathkour, H. “Selection criteria for text mining approaches.” Computers in Human Behavior, 51, 729-733. 2015
Wolfert, Sjaak, et al. “Big data in smart farming–a review.” Agricultural systems 153, pp. 69-80. 2017
Pham, Xuan, and Martin Stack. “How data analytics is transforming agriculture.” Business horizons 61.1, pp. 125-133. 2018
Goel, Raj Kumar, et al. “Smart agriculture–Urgent need of the day in developing countries.” Sustainable Computing: Informatics and Systems 30, pp. 100512. 2021
Ansari, Nazneen, et al. “Agro Advisory System Using Big Data Analytics.” Inventive Communication and Computation-al Technologies. Springer, Singapore, pp. 91-101. 2021
Shankar, Sudha, et al. “A data analytics framework for decision-making in agriculture.” Advances in Data Sciences, Security and Applications. Springer, Singapore, pp. 85-98. 2021
Sharma, Rohit, Shreyanshu Parhi, and Anjali Shishodia. “Industry 4.0 applications in agriculture: cyber-physical agri-cultural systems (CPASs).” Advances in Mechanical Engineering. Springer, Singapore, pp. 807-813. 2021
Alfred, Rayner, et al. “Towards Paddy Rice Smart Farming: A Review on Big Data, Machine Learning and Rice Production Tasks.” IEEE Access. 2021
Araújo, Sara Oleiro, et al. “Characterising the Agriculture 4.0 Landscape—Emerging Trends, Challenges and Opportuni-ties.” Agronomy 11.4, pp. 667. 2021
Gohil, Jay, et al. “Advent of Big Data technology in environment and water management sector.” Environmental Sci-ence and Pollution Research. pp. 1-19. 2021
Shrivastava, Swapnil, and Supriya N. Pal. “A Framework for Next Generation Agricultural Marketing System in Indian Context.” IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE). IEEE, 2019
Lassoued, Rim, et al. "Expert Insights on the Impacts of, and Potential for, Agricultural Big Data." Sustainability 13.5, pp. 2521. 2021
Garbero, Alessandra, Bia Carneiro, and Giuliano Resce. “Harnessing the power of machine learning analytics to under-stand food systems dynamics across development projects.” Technological Forecasting and Social Change 172, pp. 121012. 2021
Wang, Hui. “Empowerment of Digital Technology to Improve the Level of Agricultural Economic Development based on Data Mining.” 5th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2021
Vanshika, A., Kuber, B. R., & Poojitha, N. “Revolutionizing Water Quality Monitoring: The Smart Tech Frontier.” In In-novations in Machine Learning and IoT for Water Management (pp. 152-171) IGI Global. 2024
Huo, D., Malik, A. W., Ravana, S. D., Rahman, A. U., & Ahmedy, I. “Mapping smart farming: Addressing agricultural challenges in data-driven era.” Renewable and Sustainable Energy Reviews, 189, 113858. 2024
Amini, M., & Rahmani, A. “Agricultural databases evaluation with machine learning procedure.” Australian Journal of Engineering and Applied Science, 8(2023), 39-50. 2023
Purcell, W., Neubauer, T., & Mallinger, K. “Digital Twins in agriculture: Challenges and opportunities for environmental sustainability.” Current Opinion in Environmental Sustainability, 61, 101252. 2023
Javaid, M., Haleem, A., Khan, I. H., & Suman, R. “Understanding the potential applications of Artificial Intelligence in Agriculture Sector.” Advanced Agrochem, 2(1), 15-30. 2023
Pallathadka, Harikumar, et al. “Impact of machine learning on management, healthcare and agriculture.” Materials Today: Proceedings. 2021
Roberts, Daniel P., et al. “Precision agriculture and geospatial techniques for sustainable disease control.” Indian Phytopathology, pp. 1-19. 2021
Nunes, Simão AS, et al. “Cities go smart! : A system dynamics-based approach to smart city conceptualization.” Jour-nal of Cleaner Production. pp. 127683. 2021
Agbozo, Ebenezer, and Kamen Spassov. “Establishing efficient governance through data-driven e-government.” Pro-ceedings of the 11th International Conference on Theory and Practice of Electronic Governance. 2018
AlSayegh, Ahmed, Chowdhury Hossan, and Bret Slade. “Radical improvement of e-government services in Dubai.” International Journal of Services Technology and Management 25.1, pp. 53-67. 2019
Kumar, Shiv, et al. “Advance e-governance system.” International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). IEEE, 2017
Al-Dmour, H., Saad, N., Basheer Amin, E., Al-Dmour, R., & Al-Dmour, A. “The influence of the practices of big data analytics applications on bank performance: filed study.” VINE Journal of Information and Knowledge Management Systems, 53(1), 119-141. 2023
Vasa, J., Yadav, H., Patel, B., & Patel, R. “Architecture, Applications and Data Analytics Tools for Smart Cities: A Technical Perspective.” In Sentiment Analysis and Deep Learning: Proceedings of ICSADL 2022 (pp. 859-873). Singapore: Springer Nature Singapore. 2023
Samuel, P., Reshmy, A. K., Rajesh, S., Kanipriya, M., & Karthika, R. A. (2023). “AI-Based Big Data Algorithms and Machine Learning Techniques for Managing Data in E-Governance.” In AI, IoT, and Blockchain Breakthroughs in E-Governance (pp. 19-35). IGI Global
Bibri, S. E., Krogstie, J., Kaboli, A., & Alahi, A. “Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review.” Environmental Science and Eco-technology, 19, 100330. 2024
Gubareva, R., & Lopes, R. P. “Literature Review on the Smart City Resources Analysis with Big Data Methodologies.” SN Computer Science, 5(1), 152. 2024
Malhotra, Charru, Rashmi Anand, and Shauryavir Singh. “Applying big data analytics in governance to achieve sustainable development goals (SDGs) in India.” Data Science Landscape. Springer, Singapore, pp. 273-291. 2018
Marathe, Aboli, et al. “Big Data Analytics for Sustainable Cities: Pune Tree Census Data Exploratory Analysis.” 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2020
Mishra, Brojo Kishore, Abhaya Kumar Sahoo, and Rachita Misra. “Recommendation for selecting smart village in India through opinion mining using big data analytics.” ICT based innovations. Springer, Singapore, pp. 105-112. 2018
Javed, Ahmad Sayed. “Total e-Governance: Pros & Cons.” International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2018
Peisker, Anu, and Soumya Dalai. “Data analytics for rural development.” Indian Journal of Science and Technology 8.S4, pp. 50-60. 2015
Elisa, N., Yang, L., Chao, F. et al. “A framework of blockchain-based secure and privacy-preserving E-government system.” Wireless Netw 29, 1005–1015 (2023)
Kim, Eun Sun, Yunjeong Choi, and Jeongeun Byun. “Big Data Analytics in Government: Improving Decision Making for R&D Investment in Korean SMEs.” Sustainability 12.1, pp. 1-1. 2019
Cantuarias-Villessuzanne, Carmen, Romain Weigel, and Jeffrey Blain. “Clustering of European Smart Cities to Under-stand the Cities’ Sustainability Strategies.” Sustainability 13.2, pp. 513. 2021
Kim, Nammi, and Seungwoo Yang. “Characteristics of Conceptually Related Smart Cities (CRSCs) Services from the Perspective of Sustainability.” Sustainability 13.6, pp. 3334. 2021
Yoo, Yejin. “Toward Sustainable Governance: Strategic Analysis of the Smart City Seoul Portal in Korea.” Sustainability 13.11, pp. 5886. 2021
Liu, Lingyan. “Green urban environmental sustainability and health sport based on MapReduce fitness big data and ZigBee technology.” Environmental Technology & Innovation, pp. 101676. 2021
Wan, Ling, and Xiaozhong Yu. “Research on the Operation and Management Mechanism of the PPP Mode of the Smart City Construction Projects in the Era of Big Data.” International Conference on Management Science and Engi-neering Management. Springer, Cham, 2021
Zhang, Jun, et al. “Delineation of the Urban-Rural Boundary through Data Fusion: Applications to Improve Urban and Rural Environments and Promote Intensive and Healthy Urban Development.” International Journal of Environmental Research and Public Health 18.13, pp. 7180. 2021
Yin, Jiadi, et al. “Decision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping.” Remote Sensing 13.8, pp. 1579. 2021
Ying, Sun. “Research on government affairs publicity of provincial government websites in big data environment.” International Conference on Public Management and Intelligent Society (PMIS). IEEE, 2021
Zhang, Jianan, and Shuoyi Zhu. “Research on the Transfer of Rural Labor Force under the Construction of Intelligent Society” International Conference on Public Management and Intelligent Society (PMIS). IEEE, 2021
Jain, Monica. “India’s struggle against malnutrition—is the ICDS program the answer?” World Development 67, pp. 72-89. 2015
Augsburg, Britta, and Paul Andres Rodriguez-Lesmes. “Sanitation and child health in India.” World Development 107, pp. 22-39. 2018
Renugadevi, N., S. Saravanan, and CM Naga Sudha. “Revolution of Smart Healthcare Materials in Big Data Analytics.” Materials Today: Proceedings. 2021
Kohli, Neha, et al. Reprint of" What will it take to accelerate improvements in nutrition outcomes in Odisha? Learning from the past". Global food security 13, pp. 38-48. 2017
Kumar, Neha, et al. “Pathways from women's group-based programs to nutrition change in South Asia: A conceptual framework and literature review.” Global food security 17, pp. 172-185. 2018
Fletcher, R., et al. “Development of smart phone-based child health screening tools for community health workers.” IEEE Global Humanitarian Technology Conference (GHTC). IEEE, 2017. 62
Gupta, Shalu, and Pooja Tripathi. “An emerging trend of big data analytics with health insurance in India.” International Conference on Innovation and Challenges in Cyber Security (ICICCS-INBUSH). IEEE, 2016
Hore, Sirshendu, and Tanmay Bhattacharya. “Analyzing social trend towards girl child in India: a machine intelligence-based approach.” Recent Developments in Machine Learning and Data Analytics. Springer, Singapore, pp. 43-50. 2019
Ogbo, Felix Akpojene, et al. “Enablers and barriers to the utilization of antenatal care services in India.” International journal of environmental research and public health 16.17, pp. 3152. 2019
Dhami, Mansi Vijaybhai, et al. “Understanding the Enablers and Barriers to Appropriate Infants and Young Child Feeding Practices in India: A Systematic Review.” Nutrients 13.3 , pp. 825. 2021
Park, Myung-Bae, Ju Mee Wang, and Bernard E. Bulwer. “Global Dieting Trends and Seasonality: Social Big-Data Analy-sis May Be a Useful Tool.” Nutrients 13.4, pp. 1069. 2021
Song, Malin, et al. “How would big data support societal development and environmental sustainability? Insights and practices.” Journal of Cleaner Production 142, pp. 489-500. 2017
Tanwar, Harshita, and Misha Kakkar. “Performance comparison and future estimation of time series data using pre-dictive data mining techniques.” International Conference on Data Management, Analytics and Innovation (ICDMAI). IEEE, 2017
Pratap, Maheshwar, et al. “Employment guarantee scheme through the lens of financial inclusion” International Conference on Data Management, Analytics and Innovation (ICDMAI). IEEE, 2017
Malik, Garima, et al. “E-alive: An Integrated Platform Based on Machine Learning Techniques to Aware and Educate Common People with the Current Statistics of Maternal and Child Health Care.” Data Science and Big Data Analytics. Springer, Singapore, pp. 29-42. 2019
Naccarato, Alessia, et al. “Combining official and Google Trends data to forecast the Italian youth unemployment rate.” Technological Forecasting and Social Change 130, pp. 114-122. 2018
Ahmed, Hamed MS, and Yimer Ayalew Ahmed. “Constraints of youth entrepreneurs in Ethiopia” Journal of Global Entrepreneurship Research. 1-10. 2021
Katris, Christos. “Unemployment and COVID-19 Impact in Greece: A Vector Autoregression (VAR) Data Analysis.” En-gineering Proceedings 5.1, pp. 41. 2021
Bal-Domańska, Beata. “The impact of macroeconomic and structural factors on the unemployment of young women and men.” Economic Change and Restructuring. pp. 1-32. 2021
Mohan, Anandan, et al. “Informing primi and elderly pregnant women about iron sucrose administration for moder-ate anemia can improve treatment compliance in public health facilities, Kancheepuram health district, Tamil Nadu, India, 2017: A cross-sectional study.” Clinical Epidemiology and Global Health 10 , pp. 100681. 2021
Vijay, Jyoti, and Kamalesh Kumar Patel. “Recommendations to scale up dietary diversity data at household and individual level in India.” Diabetes & Metabolic Syndrome: Clinical Research & Reviews, pp. 102310. 2021
Masavah, Vincent, et al. “Open Government Data Support for the Awareness of Employment Opportunities Among the Youth in Alexandra Township in Gauteng Province in South Africa.” IST-Africa Conference (IST-Africa). IEEE, 2021
Pesquera Alonso, Carlos, Práxedes Muñoz Sánchez, and Almudena Iniesta Martínez. “Youth Guarantee: Looking for Explanations.” Sustainability 13.10, pp. 5561. 2021
Mulero, Rodrigo, and Alfredo García-Hiernaux. “Forecasting Spanish unemployment with Google Trends and dimension reduction techniques.” SERIEs, pp. 1-21. 2021
Burns, Courtney Julia, Keiko Chen, and Hanni Stoklosa. "Pushing for the same thing on the same set of tracks: a qualitative study exploring the anti-trafficking response in Bihar and Uttar Pradesh." BMC public health 21 (2021): 1-10
Cederbaum, Julie A., et al. “Using the Theory of Reasoned Action to examine grandparent and maternal substance use on the cannabis use of children of teen mothers.” Drug and Alcohol Dependence 228, pp. 109019. 2021
Marimbire, B., Al-Nahari, A., Ahmadzai, W. K., Al-Jumeily, D., & Khan, W. “Predicting the Effectiveness of ‘Stop and Search’Police Interventions Using Advanced Data Analytics.” In 2023 15th International Conference on Developments in eSystems Engineering (DeSE) (pp. 202-208). IEEE. 2023
Kiganda, C., & Akcayol, M. A. “Forecasting the spread of COVID-19 using deep learning and big data analytics meth-ods.” SN Computer Science, 4(4), 374. 2023
Neto, Cristiana, et al. “Data Mining Approach to Understand the Association Between Mental Disorders and Unemployment.” International Conference on Information Technology & Systems. Springer, Cham, 2021
Awotunde, Joseph Bamidele, et al. “Big Data and Data Analytics for an Enhanced COVID-19 Epidemic Management.” Artificial Intelligence for COVID-19. Springer, Cham, pp. 11-29. 2021
Marshall, Vanessa, et al. “The Focus They Deserve: Improving Women Veterans’ Health Care Access.” Women's Health Issues. 2021
