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Smart beta investing in India portfolio construction implementation and evaluation
The smart beta strategies, having marked their footprint in the developed markets in the last decades on the backdrop of the failure of active investing, are capturing emerging markets such as India recently. In this regard, the study attempts to examine the performance of smart beta strategies in long-only, multifactor, and alternative indexing frameworks in India. The study builds alternatively weighted (AW) univariate portfolios. Firstly, the cap-weighted (CW) single-factor portfolios are built. Subsequently, the portfolios are alternatively weighted and compared to the CW portfolio. Next, the CW multifactor portfolios are built and compared with singlefactor portfolios. Finally, the AW multifactor portfolios are built and newlinecompared with CW multifactor portfolios. All the portfolios are tested for their significant performance relative to the risk-free rate, market, and alpha under factor models. The portfolios were constructed from the constituents of NIFTY 500, adjusting for survivorship bias. The sample period spanned over 21 years from 01/10/2000 to 31/09/2021. The hypotheses were tested using the One-Sample T-test or Wilcoxon Signed Rank test for the difference in return, based on return distribution, and the Wald test for the difference in alpha and exposure using the Seemingly Unrelated Regression framework. The portfolios were constructed and analyzed using Python. We find mixed evidence of factor presence; the factor portfolios built on market data such as Illiquid, Winner, Stable, and Size offered better performance than those built on fundamental data such as Value, Strong, and Conservative. The Integrated portfolio does not differ from Mixed and single-factor portfolios, except for underperformance against the Illiquid portfolio. The alternative weighting offered mixed performance at single and multifactor levels. -
Smart Business and Education in the Age of VUCA and BANI
In a world increasingly characterized by volatility, uncertainty, complexity, and ambiguity (VUCA) and, more recently, brittleness, anxiety, nonlinearity, and incomprehensibility (BANI), both business and education stand at a critical crossroads. Organizations and learning institutions must now evolve to remain relevant and resilient in this turbulent landscape. The urgent need for adaptive thinking and emotional agility is essential now to navigate disruption while fostering innovation and human-centered growth. In this new era, success depends not on predicting the future, but on developing the capacity to adapt and lead through constant change. Smart Business and Education in the Age of VUCA and BANI explores how smart technologies and data-driven innovation are transforming business and education in the VUCA and BANI world. It highlights adaptive strategies, digital inclusion, and AI-driven practices in shaping sustainable and equitable futures. Covering topics such as technological advancements, business innovation, and artificial intelligence, this book is an excellent resource for academicians, researchers, business leaders, global economists, educational administrators and leaders, policymakers, educators, and more. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Smart car - accident detection and notification using amazon alexa
The high demand for automobiles has increased traffic hazards and road accidents. Life of the people is under high risk. This is because of the lack of the best emergency facilities available in the country. The proposed system can detect accidents in significantly less time and sends the basic information first to aid center and relatives of the victim on mobile and Amazon Alexa within a few seconds covering geographical coordinates. Various devices like Arduino UNO for car movement demonstration, Arduino Mega for accident detection and Raspberry Pi 3B for internet services gateway, accelerometer and impact sensor working together to detect an accident. All connected over the internet to generate a huge amount of data which holds a lot of information about the occurrence of the accident based on the speed and location and can be used to detect accident hotspots. The system also focuses on the safety of pedestrians where a safety band is programmed to perform the notification services using an emergency push button. The ESP8266 NodeMCU invokes the same services using a button on the module. The data generated may be used for the prediction, analysis to prevent future accidents and contribute to future road safety. Springer Nature Switzerland AG 2020. -
Smart Certificates Using Blockchain: A Review
When making job offers, it is usual practice for businesses to check applicants academic credentials. The organization that issued the certificate must authenticate it for the employer to ensure that it is genuine. Because of the lengthy process involved in certificate verification, the selection process takes longer overall while establishing the legitimacy of a certificate. To address this issue, blockchain provides a verified distributed ledger along with a cryptography mechanism to thwart academic credential counterfeiting. The Blockchain also provides a standardized platform for document access, storage, and verification that takes the least amount of time. The review of the methodologies and performance of the same has been covered in the paper. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Smart cities: Redefining urban life through IoT
A smart city is designed using acceptable internet of things (IoT) technologies that solve urban life problems and provide quality of life to the residents. IoT refers to a network of physical devices that are capable of gathering and sharing data and expediting numerous functions without human assistance. IoT supports smart home builders and managers by providing an efficient ecosystem in terms of less operating cost and improvising residence services. In recent days, the initiative of smart homes/buildings/ cities is increasing gradually around the globe. The inclined population in an urban area also expects well-managed automated services in their everyday life. 2023, IGI Global. -
Smart City Governance and Citizen Engagement
The smart city idea has been put into practice in numerous nations as a response to urban issues. With the ultimate goal of improving quality of life and well-being, smart cities are more and more eager to engage in fruitful dialogue with their residents, better understand their demands, and develop digital platforms for inciting collaborative initiatives between authorities and people. Prior researches have noted challenges with execution and the importance of smart citizens as key components of a smart city. Using an internet-based social platform, this project intends to learn more about how smart cities are implemented and how citizens are involved. Smart city development should be modified to account for local conditions. Local expertise, transformative leadership, sustainability, and political content are the key success criteria for the implementation. Through an online social network, city residents have been participating in the implementation of the smart city. In order to make sure that city citizens are motivated to address the citys challenges, a sort of incentive structure remains necessary. Previous research efforts were conducted in an effort to measure the projects effectiveness by achieving benefits. The people of that country are the end users of public infrastructure projects. Nevertheless, communities all throughout the world have struggled to achieve genuine citizen engagement. This component of citizen engagement has been highlighted as a crucial goal to be accomplished. This chapter examines the role of AI in citizen engagement and participation in the smart city implementation. The chapter also intends to analyse the relevant research works to examine the trends in smart city governance and AI. This study will provide also insights into emerging issues and challenges. 2025 selection and editorial matter Pawan Whig, Pavika Sharma, Nagender Aneja, Ahmed A. Elngar and Nuno Silva; individual chapters, the contributors. -
Smart city initiatives and disaster resilience of cities through spatial planning in Pune city, India
Cities are attracting populations at alarming rate. Cities provide the need of populations in every way from livelihoods to livability. In doing so it is exhausting its resources resulting in increasing threats of risk. An initiative like Smart City Mission is aiming to enhance the capacities of the cities to increase livability and quality of life for its population and decrease threats of risk. This study examines the impact of smart city initiatives on resilience to earthquakes and floods through a spatial planning perspective for the city of Pune in State of Maharashtra through series of structured interviews with key stakeholders. The findings suggest that smart city initiative is still in its primary stage and requires assimilation with the development strategy to contribute to the resilience of the city. The study further proposes the need to integrate the smart city initiative with all the current and future developmental projects. 2023, World Research Association. All rights reserved. -
Smart Cyber-Physical Systems: Innovations and Real-World Implications
Smart cyber-physical systems (SCPS) are revolutionizing the interaction between the physical and digital realms, driving innovation across diverse fields. This book provides an extensive overview of cutting-edge SCPS technologies, highlighting their applications, challenges, and transformative potential. Designed for researchers, professionals, and students, it offers foundational insights and advanced applications in urban planning, healthcare, transportation, finance, and cybersecurity. It also bridges the gap between theory and practice through real-world case studies and in-depth analysis, showcasing how SCPS address critical global challenges. This book: Provides a comprehensive introduction to SCPS, their components, and their applications in various domains and explores their role in enabling sustainable smart cities and urban planning Provides advanced SCPS-based solutions for optimizing supply chain logistics and route planning and real-world applications of SCPS in healthcare, including wearable technology and remote patient monitoring, and financial modeling, comparing investment indices using advanced techniques Discusses the integration of artificial intelligence and machine learning in autonomous vehicle systems and transportation Analyzes cybersecurity challenges in cryptocurrency and blockchain ecosystems Focuses on innovations in energy management, including smart grids and sustainable practices powered by SCPS, and explores adaptive human-machine interaction frameworks for enhanced decision-making. This book serves as a vital resource for understanding the transformative power of SCPS and inspires further research and development in this dynamic and rapidly evolving field. 2026 selection and editorial matter, Ramesh Chandra Poonia, Kamal Upreti and Mohammad S. Khan. All rights reserved. -
Smart detection of rice purity and its grading
The main food in India is Rice. Be it the breakfast, lunch, dinner or some snacks, for everything the most preferred ingredient in Rice. In compared with north Indians, Rice is most used by South Indians. Today's youngsters from villages are migrating to cities in search of jobs after their education. Even farmers have stopped their cultivation and are working towards different business. So, the yield of rice is reduced in India. One more reason for this is because of the poor monsoon. Government is finding it challenging to supply rice to all its consumers. It is expected, because for Rice the consumers are more compared to its production. Government has decided to import the rice from the neighboring countries. This neighboring country knows the demand of rice in India and started supplying contaminated rice. Currently our Government has no technology to check the quality of the rice which they are getting imported, so the result is plastic rice arrived in India. Indirectly, India is in huge loss in terms of money and damages for its citizens health. So, there is a need of automated system to detect the quality of the rice that are imported. Another use of such automated system is that most of the people are not able to identify the type of the rice and the quality of the rice. This system helps even common man a facility in identifying the type and quality of rice. 2017 IEEE. -
Smart Edge Computing for 5g/6g Satellite IOT for Reducing Inter Transmission Delay
5G/6G communication are first generation high speed wireless communication network which integrates the aerial data, terrestrial data and maritime data via satellite to IoT cellular devices. Technological motivation tends to increase the satellites day by day for supporting most of global applications. These applications highly relay on satellite data for processing users request and giving appropriate outcome to the users. World grows very fastly with new technologies which makes demand for fastest data communication. Handling the satellite IoT data is worthiest research problem and it must be paid with more attention. At present inter satellite communication face high delay with lower data utilization rate. The effective utilization of data generated by satellite IoT is processed using our proposed intelligent model called smart edge computing (SEC-5G) for 5G. The SEC-5G embeds with satellite for reducing the data transfer limitation and delay in inter satellite communication. In this research we highly concentrate on satellite IoT data and its problem. Our proposed system reduces the limitation in inter satellite data communication rate which makes higher delay in data processing and utilization. In this article, smart edge computing is designed for satellite IoT using SDN/NFV and deep convolutional neural network (DCNN) with logical ring construction. The task uses SDN/NFV model to choose edge node, cloud node in the smart edge computing. Based on training data, DCNN works on SEC-5G software model. Smart architecture helps to increase the performance, scalability, reliability of satellite edge computing model. This architecture works with machine learning model and helps to improve the future satellite speed on data processing. The performance of the proposed is compared with existing Ground 5G. Evaluated outcome shows proposed embedded satellite outperforms in data communication. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Smart Embedded Framework of Real-Time Pollution Monitoring and Alert System
The sustainability and progress of humanity depend on a clean, pollution-free environment, which is essential for good health and hygiene. Huge indoor auditorium does not have proper ventilation for air flow so when the auditorium is crowded the carbon di-oxide is emitted and it stays there for many days this may be a chance to spreading of COVID-19 and other infectious diseases. Without proper ventilation virus may present in the indoor auditorium. In the proposed system, emissions are detected by air, noise, and dust sensors. If the signal limit is exceeded, a warning is given to the authorities via an Android application and WiFi, and data is stored in cloud networks. In this active system, CO2 sensor, noise sensor, dust sensor, Microcontroller and an exhaust fan are used. This ESP-32 based system is developed in Arduino Integrated Development Environment (Aurdino IDE) to monitor air, dust and noise pollution in an indoor auditorium to prevent unwanted health problems related to noise and dust. More importantly, using IoT Android Application is developed in Embedded C, which continuously records the variation in levels of 3 parameters mentioned above in cloud and display in Android screen. Also, it sends an alert message to the users if the level of parameters exceeds the minimum and maximum threshold values with more accuracy and sensitivity. Accuracy and sensitivity of this products are noted which is very high for various input values. 2022 IEEE. -
Smart Facial Emotion Recognition with Gender and Age Factor Estimation
Human-Computer Interaction (HCI) in an intelligent way, which aims at creating scalable and flexible solutions. Big tech firms and businesses believe in the success of HCI as it allows them to profit from on-demand technology and infrastructure for information-centric applications without having to use public clouds. Because of its capacity to imitate human coding abilities, facial expression recognition and software-based facial expression identification systems are crucial. This paper proposes a system of recognizing the emotional condition of humans, given a facial expression, and conveys two methods of predicting the age and gender factors from human faces. This research also aims in understanding the influences posed by gender and age of humans on their facial expressions. The model can currently detect 7 emotions based on the facial data of a person - (Anger, Disgust, Happy, Fear, Sad, Surprise, and Neutral state). The proposed system is divided into three segments: a.) Gender Detection b.) Age Detection c.) Emotion Recognition. The initial model is created using 2 algorithms - KNN, and SVM. We have also utilized the architectures of some of the deep learning models such as CNN and VGG - 16 pre-trained models (Transfer Learning). The evaluation metrics show the model performance regarding the accuracy of the Recognition system. Future enhancements of this work can include the deployment of the DL and ML model onto an android or a wearable device such as a smartphone or a watch for a real-time use case. 2022 Elsevier B.V.. All rights reserved. -
Smart Facial Expression Analysis: Fuzzy Extreme Learning Machine in Emotion Detection
The immense academic and economic potential of facial emotion recognition (FER) has made it a crucial field in computer vision and artificial intelligence. Because of the fundamental role that facial expressions play in interpersonal communication; face photographs are vital for analysing human emotions within the context of Smart Facial Expression Analysis. This research provides a successful pipeline for emotion identification and examines FER methods that rely just on face pictures. Preprocessing, segmentation, feature extraction, and training the model are the steps that make up the suggested method's organised procedure. Face detection using the Viola-Jones technique is the first step in the preprocessing phase. Four rectangular characteristics are used for segmentation, with greyscale conversion being a necessity. In order to train a fuzzy -ELM model, feature extraction uses HOS and LBP. Emotions are better understood with this method. The suggested fuzzy-ELM approach outperforms two state-of-the-art models, ELM and CNN. With an accuracy of 98.33 %, the experimental findings show a substantial improvement in precision. A dependable and high-performing method for emotion recognition using just facial imaging, these findings highlight the usefulness of the suggested approach for Smart Facial Expression Analysis. 2025 IEEE. -
Smart Farming with Ensemble Learning: A Soil-Driven Crop Suggestion Model for Sustainable Agriculture
The use of machine learning (ML) in agriculture has paved new avenues to improve decision making, especially in crop choice. The current research offers a data-driven crop recommendation system using a machine learning approach based on key soil and environmental factorsi.e., nitrogen (N), phosphorus (P), potassium (K), pH, temperature, humidity, and rainfall. A dataset of 2,200 soil records was processed using exploratory data analysis (EDA), normalization, and model training with algorithms such as Random Forest, Logistic Regression, and Gradient Boosting. Of these, Random Forest provided the best test accuracy of 99.32%, with high predictive ability and interpretability via feature importance measures. Violin and boxplots showed distinct feature separability among crop types, particularly in variables such as rainfall, temperature, and NPK concentrations, confirming the model's classification effectiveness. The practicability of the system is in its possible incorporation in IoT-based soil monitoring devices and cell advisory apps, delivering real-time, location-specific crop advice. This strategy enables farmers to make informed decisions, minimizes fertilizer waste, and promotes sustainable farming practices. The suggested system not only showcases technical strength but also fits well within the overall vision of smart farming and precision agriculture. Author(s) 2025. -
Smart Finances: A Web-Based System for Personalized Financial Management
Smart Finances is a dynamic and user-friendly web application designed to assist users in managing and understanding their personal finances with ease. Built using HTML, CSS, JavaScript, and PHP with MySQL for backend functionality and data persistence, the platform offers a suite of tools, including an interest calculator, investment calculator, budget manager, and interactive spending analysis. The intuitive interface enhances usability and promotes financial literacy, especially among students and individuals new to personal finance. The application supports both guest and registered user modes, offering tiered access to features based on authentication. Smart Finances aims to make money management more approachable and insightful through accessible design and practical functionality. Initial user testing with 20 participants indicated a 30% improvement in budgeting accuracy and a high satisfaction rate (88%) with the usability of the interface. These results validate the systems impact on financial literacy and user engagement. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Smart grid and energy management in smart cyber-physical systems (SCPS)
[No abstract available] -
Smart healthcare system design: Security and privacy aspects
SMART HEALTHCARE SYSTEM DESIGN This book deeply discusses the major challenges and issues for security and privacy aspects of smart health-care systems. The Internet-of-Things (IoT) has emerged as a powerful and promising technology, and though it has significant technological, social, and economic impacts, it also poses new security and privacy challenges. Compared with the traditional internet, the IoT has various embedded devices, mobile devices, a server, and the cloud, with different capabilities to support multiple services. The pervasiveness of these devices represents a huge attack surface and, since the IoT connects cyberspace to physical space, known as a cyber-physical system, IoT attacks not only have an impact on information systems, but also affect physical infrastructure, the environment, and even human security. The purpose of this book is to help achieve a better integration between the work of researchers and practitioners in a single medium for capturing state-of-the-art IoT solutions in healthcare applications, and to address how to improve the proficiency of wireless sensor networks (WSNs) in healthcare. It explores possible automated solutions in everyday life, including the structures of healthcare systems built to handle large amounts of data, thereby improving clinical decisions. The 14 separate chapters address various aspects of the IoT system, such as design challenges, theory, various protocols, implementation issues, as well as several case studies. Smart Healthcare System Design covers the introduction, development, and applications of smart healthcare models that represent the current state-of-the-art of various domains. The primary focus is on theory, algorithms, and their implementation targeted at real-world problems. It will deal with different applications to give the practitioner a flavor of how IoT architectures are designed and introduced into various situations. Audience: Researchers and industry engineers in information technology, artificial intelligence, cyber security, as well as designers of healthcare systems, will find this book very valuable. 2021 Scrivener Publishing LLC. All rights reserved. -
Smart Healthcare Systems and Artificial Intelligence: Leveraging Data-Driven Solutions in Healthcare
Smart healthcare systems, powered by artificial intelligence (AI), enables drastic shift in healthcare sector. The benefits of data-driven solutions anchored in advanced disease diagnosis, efficient administrative records management, and operational efficiency. AI algorithms, including machine learning and deep learning, enable real-time data analysis from diverse sources such as Internet of medical Things (IoMT), wearable devices, and medical imaging. This facilitates early disease detection, personalized treatment plans, and predictive analytics, leading to improved health outcomes. Additionally, AI-powered systems optimize resource management, reduce human error, and streamline administrative tasks. While challenges such as data privacy, integration complexities, and ethical concerns exist, the potential of smart healthcare systems to revolutionize healthcare delivery is undeniable. This study explores the role of AI in advancing smart healthcare, focusing on the integration of data-driven technologies to create a more efficient, accessible, and patient-centered healthcare ecosystem. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.