Machine learning for smart city AI systems Manasvi Logani, Sandhya Makkar Handbook of Artificial Intelligence for Smart City Development Management Systems and Technology Challenges, 2025 Due to continued urbanization and modernization, smart cities have become our future. In smart cities, it is of significance to harness the technologies to create advanced lifestyles at an affordable cost sustainably. For reaching this level of growth, a huge volume of data is required, i.e., big data which is prone to errors and can be of labelled and unlabelled type. To leverage this data for development, machine learning plays a huge role. The use of machine learning depends on the data being labelled for supervised learning to find specific solutions in the collected raw data or unlabelled for unsupervised learning to find solutions by recognizing underlying patterns/anomalies. This chapter focuses on advanced machine learning algorithms and their ability to handle the diverse data collected efficiently to provide solutions. Also, the applications of these algorithms in a smart city like traffic management, pollution control, energy conservation, healthcare and public security will be of concern here.
Customer Sentiments in Product Reviews: A Comparative Study with GooglePaLM Olamilekan Shobayo, Swethika Sasikumar, Sandhya Makkar, Obinna Okoyeigbo Analytics, 2024 In this work, we evaluated the efficacy of Google’s Pathways Language Model (GooglePaLM) in analyzing sentiments expressed in product reviews. Although conventional Natural Language Processing (NLP) techniques such as the rule-based Valence Aware Dictionary for Sentiment Reasoning (VADER) and the long sequence Bidirectional Encoder Representations from Transformers (BERT) model are effective, they frequently encounter difficulties when dealing with intricate linguistic features like sarcasm and contextual nuances commonly found in customer feedback. We performed a sentiment analysis on Amazon’s fashion review datasets using the VADER, BERT, and GooglePaLM models, respectively, and compared the results based on evaluation metrics such as precision, recall, accuracy correct positive prediction, and correct negative prediction. We used the default values of the VADER and BERT models and slightly finetuned GooglePaLM with a Temperature of 0.0 and an N-value of 1. We observed that GooglePaLM performed better with correct positive and negative prediction values of 0.91 and 0.93, respectively, followed by BERT and VADER. We concluded that large language models surpass traditional rule-based systems for natural language processing tasks.
Machine Learning for Smart City AI Systems Manasvi Logani, Sandhya Makkar Handbook of Artificial Intelligence for Smart City Development Management Systems and Technology Challenges, 2024 Due to continued urbanization and modernization, smart cities have become our future. In smart cities, it is of significance to harness the technologies to create advanced lifestyles at an affordable cost sustainably. For reaching this level of growth, a huge volume of data is required, i.e., big data which is prone to errors and can be of labelled and unlabelled type. To leverage this data for development, machine learning plays a huge role. The use of machine learning depends on the data being labelled for supervised learning to find specific solutions in the collected raw data or unlabelled for unsupervised learning to find solutions by recognizing underlying patterns/anomalies. This chapter focuses on advanced machine learning algorithms and their ability to handle the diverse data collected efficiently to provide solutions. Also, the applications of these algorithms in a smart city like traffic management, pollution control, energy conservation, healthcare and public security will be of concern here.
Handbook of artificial intelligence for smart city development: management systems and technology challenges S Makkar, G Ravindran, RK Chakrabortty, A Pal CRC Press , 2025 2025 Citations: 5
Machine Learning for Smart City AI Systems M Logani, S Makkar Handbook of Artificial Intelligence for Smart City Development, 1-26 , 2025 2025 Citations: 3
Customer sentiments in product reviews: a comparative study with GooglePaLM O Shobayo, S Sasikumar, S Makkar, O Okoyeigbo Analytics 3 (2), 241-254 , 2024 2024 Citations: 12
Object detection for helping visually impaired S Makkar, S Joshi, T Gupta, R Kannan, K Dhandapani AIP Conference Proceedings 2971 (1), 020068 , 2024 2024
Best third-party logistics service provider for an ecommerce food delivery company using analytical hierarchy process S Makkar, S Verma, R Kannan, P Billa, F Selvaraj, A Razak AIP Conference Proceedings 2971 (1), 060026 , 2024 2024
Human resource information system applications in small and medium enterprises: A study (SMEs) D Singh, S Makkar, S Durai, G Manoharan, S Purushottamashtikar, ... AIP conference proceedings 2971 (1), 060036 , 2024 2024 Citations: 7
The impact of information technology enabler and organizational learning on performance: A systematic literature review D Singh, S Makkar, G Manoharan, S Durai, S Purushottamashtikar, ... AIP Conference Proceedings 2971 (1), 060027 , 2024 2024 Citations: 8
Impact of trade deficit on defence expenditure H Tandon, S Maheshwari, S Makkar, G Manoharan AIP Conference Proceedings 2418 (1), 020028 , 2022 2022 Citations: 2
Implementation of blockchain in supply chain N Gulati, A Sethi, D Mahesh, S Makkar, G Manoharan, Megaladevi, ... AIP conference proceedings 2418 (1), 020026 , 2022 2022 Citations: 12
Blockchain disruption in banking sector S Makkar, T Bajpai, M Bhola, D Mahesh, G Manoharan AIP conference proceedings 2418 (1), 020019 , 2022 2022 Citations: 11
Predicting air passenger traffic during Covid-19 & its economic impact S Makkar, A Khan, A Lal, G Manoharan AIP conference proceedings 2418 (1), 020032 , 2022 2022 Citations: 5
Predictive analytics on e-commerce annual sales S Makkar, S Jaiswal Proceedings of Data Analytics and Management: ICDAM 2021, Volume 1, 557-567 , 2022 2022 Citations: 5
IoT applications in landslide prediction and abatement—Trends, opportunities, and challenges U Sinthuja, S Thavamani, S Makkar, R Gobinath, E Gayathiri Computers in Earth and Environmental Sciences, 319-325 , 2022 2022 Citations: 10
Soft computing applications in rainfall-induced landslide analysis and protection—Recent trends, techniques, and opportunities AA Salunkhe, R Gobinath, S Makkar Computers in Earth and Environmental Sciences, 271-287 , 2022 2022 Citations: 3
IoT applications in landslide prediction and abatement-Trends, opportunities U Sinthujaa, S Thavamani, S Makkar Computers in Earth and Environmental Sciences: Artificial Intelligence and … , 2021 2021
Information technology, management and operations research practices VK Solanki, S Makkar, S Agarwal (No Title) , 2021 2021
Privacy Vulnerabilities and Data Security Challenges in the IoT S Agarwal, S Makkar, DT Tran CRC Press, https://www.routledge.com/Privacy-Vulnerabilities-and-Data … , 2020 2020 Citations: 16
Detecting medical reviews using sentiment analysis S Makkar, M Singhal, N Gulati, S Agarwal Privacy Vulnerabilities and Data Security Challenges in the IoT, 199-216 , 2020 2020 Citations: 2
The Internet of Things (IoT) and Contactless Payments: An Empirical Analysis of the Healthcare Industry P Ahuja, S Makkar Privacy Vulnerabilities and Data Security Challenges in the IoT, 61-76 , 2020 2020
Applications of Industrial Internet of Things (IIoT) S Makkar, M Duseja, S Agarwal Privacy Vulnerabilities and Data Security Challenges in the IoT, 1-20 , 2020 2020 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Applications of machine learning techniques in supply chain optimization S Makkar, GNR Devi, VK Solanki International Conference on Intelligent Computing and Communication … , 2019 2019 Citations: 84
IoT based predictive maintenance in manufacturing sector S Nangia, S Makkar, R Hassan Proceedings of the International conference on innovative computing … , 2020 2020 Citations: 60
Theoretical analysis of big data for smart scenarios VK Solanki, S Makkar, R Kumar, JM Chatterjee Internet of things and big data analytics for smart generation, 1-12 , 2018 2018 Citations: 18
Privacy Vulnerabilities and Data Security Challenges in the IoT S Agarwal, S Makkar, DT Tran CRC Press, https://www.routledge.com/Privacy-Vulnerabilities-and-Data … , 2020 2020 Citations: 16
Uncovering employee job satisfaction using machine learning: A case study of om logistics ltd D Jain, S Makkar, L Jindal, M Gupta International Conference on Innovative Computing and Communications … , 2020 2020 Citations: 15
Challenges and opportunities of Internet of Things for health care S Makkar, AK Singh, SS Mohapatra A Handbook of Internet of Things in Biomedical and Cyber Physical System … , 2019 2019 Citations: 14
Customer sentiments in product reviews: a comparative study with GooglePaLM O Shobayo, S Sasikumar, S Makkar, O Okoyeigbo Analytics 3 (2), 241-254 , 2024 2024 Citations: 12
Implementation of blockchain in supply chain N Gulati, A Sethi, D Mahesh, S Makkar, G Manoharan, Megaladevi, ... AIP conference proceedings 2418 (1), 020026 , 2022 2022 Citations: 12
Blockchain disruption in banking sector S Makkar, T Bajpai, M Bhola, D Mahesh, G Manoharan AIP conference proceedings 2418 (1), 020019 , 2022 2022 Citations: 11
Single-source, single-destination, multi product EOQ model with quantity discount incorporating partial/full truckload policy S Bajaj, PC Jha, KK Aggarwal International Journal of Business Performance and Supply Chain Modelling 5 … , 2013 2013 Citations: 11
IoT applications in landslide prediction and abatement—Trends, opportunities, and challenges U Sinthuja, S Thavamani, S Makkar, R Gobinath, E Gayathiri Computers in Earth and Environmental Sciences, 319-325 , 2022 2022 Citations: 10
Predictive analytics for retail store chain S Makkar, A Sethi, S Jain International Conference on Innovative Computing and Communications … , 2020 2020 Citations: 10
The impact of information technology enabler and organizational learning on performance: A systematic literature review D Singh, S Makkar, G Manoharan, S Durai, S Purushottamashtikar, ... AIP Conference Proceedings 2971 (1), 060027 , 2024 2024 Citations: 8
Human resource information system applications in small and medium enterprises: A study (SMEs) D Singh, S Makkar, S Durai, G Manoharan, S Purushottamashtikar, ... AIP conference proceedings 2971 (1), 060036 , 2024 2024 Citations: 7
Handbook of artificial intelligence for smart city development: management systems and technology challenges S Makkar, G Ravindran, RK Chakrabortty, A Pal CRC Press , 2025 2025 Citations: 5
Predicting air passenger traffic during Covid-19 & its economic impact S Makkar, A Khan, A Lal, G Manoharan AIP conference proceedings 2418 (1), 020032 , 2022 2022 Citations: 5
Predictive analytics on e-commerce annual sales S Makkar, S Jaiswal Proceedings of Data Analytics and Management: ICDAM 2021, Volume 1, 557-567 , 2022 2022 Citations: 5
Single-Source, Multiple-Destination coordination of multi item EOQ model for perishable products with quantity discounts incorporating Partial/Full truckload policy under fuzzy … S Makkar, PC Jha Journal of Information and Optimization Sciences 33 (2-3), 385-399 , 2012 2012 Citations: 5
Procurement-distribution model for perishable items with quantity discounts incorporating freight policies under fuzzy environment S Makkar, PC Jha Yugoslav Journal of Operations Research 23 (2), 183-196 , 2013 2013 Citations: 4
Machine Learning for Smart City AI Systems M Logani, S Makkar Handbook of Artificial Intelligence for Smart City Development, 1-26 , 2025 2025 Citations: 3
