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Smart Intelligence Aided Power and Energy Management
The Artificial Intelligence (AI) has become a revolutionary technology in power and energy management, providing exceptional prospects for improving efficiency, reliability, and sustainability. This study delves into the incorporation of AI methodologies into smart intelligence-driven systems for power and energy management. It delves into how AI algorithms, encompassing machine learning and optimization approaches, are utilized to enhance energy generation, distribution, and consumption across a range of environments, including smart grids, microgrids, and intelligent buildings. The abstract examines the primary challenges and factors to consider when implementing AI-driven solutions for power and energy management, which encompass issues such as data quality, privacy, security, and scalability. It emphasizes the crucial role of transparency and interpretability in AI algorithms to cultivate trust among stakeholders and secure user acceptance. Additionally, it addresses the importance of upholding ethical standards and regulatory requirements to address societal apprehensions and mitigate potential risks linked to the deployment of AI in energy systems. Moreover, the abstract highlights AIs contribution to advancing energy efficiency and sustainability through dynamic demand response, incorporating renewable resources, and the optimization of grid operations. It underscores the importance of on-going monitoring and evaluation of AI-driven energy management systems to pinpoint areas for enhancement and mitigate unintended repercussions. In summary, this paper offers perspectives on AIs potential to transform power and energy management methodologies, leading to more intelligent, robust, and eco-friendly energy systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Smart Intelligence Perspective and Integrating AI with the Power System
The confluence of Artificial Intelligence (AI) and energy frameworks has become a focal point in contemporary research, driven by the imperative to innovate and advance our energy systems. The book chapter delves into the nuanced relationship between AI and these systems, highlighting its opportunities for improved performance, resilience, and environmental conservation. Central to this exploration is the elucidation of AIs transformative potential in energy dynamics, spanning areas such as machine learning, deep learning, neural architectures, and foresight modelling. The chapter portrays diverse AI-driven applications, emphasising their transformative capabilities in steering energy strategies. Insights into the multifaceted advantages of integrating AI into energy frameworks are presented, stressing augmented stability, amplified efficiency, fiscal savings, and forward-thinking outage resolutions. Based on real-world examples, the research highlights the value of integrating AI into energy strategies. It also identifies new paradigms in the evolving energy landscape that will shape our energy future. This underscores AIs crucial role in driving energy transformations and calls for collaboration among academia, decision-makers, and industry leaders to create a greener, more efficient energy path. The importance of data analytics in managing power system data, enabling insights into consumption trends, and assisting in making educated decisions is also covered in this chapter. In order to ensure a responsible and secure implementation, the ethical and privacy issues associated with AI deployment in the power sector are also addressed. Furthermore, the chapter elaborates on the prospective trajectory of AI within Power Systems, elucidating its involvement in quantum computing, edge computing, and the incorporation of IoT to facilitate Microgrid Management. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
Smart Intravenous Infusion Monitoring and Alert System using IoT-based Force Sensitive Resistor and Whatabot API
Intravenous fluids with vitamins are given to people who are dehydrated and have an imbalance of electrolytes. When the IV bag is empty, the patient's blood flows through the IV line toward the empty bag because their blood pressure is higher than the IV bag's. This process, called diffusion can lead to pain and loss of blood. If the IV bag is empty and hooked up to the patient, air can get into the bloodstream. The air bubble enters the patient's bloodstream, causing the same catastrophic effects. This paper aims to eliminate the danger by creating Smart IV Bags in light of the rising number of risks in the medical sector brought on by the reverse flow of blood in an IV bag (intravenous bag). The Smart IV bags eliminate the need for constant physical monitoring of the IV bag's state while preventing reverse blood flow. For detection of the IV fluid state, a 0.5 ' diameter force-sensitive resistor is deployed. We integrate the system with a NodeMCU module and using Wi-Fi, it establishes communication between the smart IV bag and the person in charge at the hospital, like a nurse or a caretaker. In this study, the IV Bag is the 'thing' connected to the internet where the FSR readings are analyzed using NodeMCU script to determine if it needs to be emptied and send a WhatsApp message to the caretaker. This design establishes an IoT environment where the IV Bag automatically alerts the caretaker and eliminates the need for constant human intervention. 2023 IEEE. -
Smart Irrigation System Using Soil Moisture Sensor
The impart of climatic change apparently affect accessibility of good water for agriculture irrigation system in addition to human dependency and demand on farm products for survival, increases water unavailability challenges in the farm affecting ecosystem when there is no balance between country food production capacity and population growth. Agricultural sector is challenged with unequal distribution of water in the farm plantations reducing food production strength, this is more severe in under-developing regions whereby require smart irrigation systems as promising solution to mitigate against threat of water distribution to farm products. This research work design and develop smart irrigation system with less expensive microcontroller components, implementing water distribution system using sensor captured information of soil condition, infusing precision irrigation system that calculate and supplies exact water require based on soil dryness level. The research adopts internet of things IoT technology where sensor will be used to monitor and capture soil information and control water distribution based on available soil dataset. The outcome of the research gives absolute control on over-irrigation and under-irrigation system that increases agricultural productions with advance technological means, precision irrigation system mechanisms reduces water wastage and ensure equal distributions. Multivariate soil type test will greatly enhance general acceptability of this concept in cross-functional regions. 2025 IEEE. -
Smart medical sensor
Medical sensors facilitate health-care applications to save a patient's life by continuously monitoring the patient's health. The combined feature of medical sensors and the fastest growing techniques that are Internet of things improves the accuracy of treatment. Internet of things techniques serve the smart and very effective medical service. Early diagnosis of the symptoms helps the health-care provider to get success in the treatment to save a patient's life. Many medical sensors are available in the health-care application that can monitor continuously patient health. Medical sensors can be wearable and nonwearable. There are some common parameters such as body temperature and a heart rate that are used to monitor human activity. These parameters are measured by using wearable and body-embedded sensors. The data collected from these parameters are analyzed by the medical devices for early detection of disease. The advanced internet of things techniques help to connect the sensors, patients, hospitals, and other medical devices. In this chapter, we highlight the use of different types of sensors with advanced technology (internet of things). 2023 Elsevier Inc. All rights reserved. -
Smart Metering System with Google Assistant
This paper presents a unique research problem in the area of automation system by using IoT. The mentioned approach utilizes Google assistant, which is incorporated within Google home which uses voice-controlled inputs and voice feedbacks. This paper discusses a new method to develop a smart energy meter at a distributor level and to make use of this technology to monitor the power consumption of each device individually which can help the user to monitor the electricity usage in real time and thus helps to save electricity and reduce cost on your electricity bill. 2020, Asian Research Association. All rights reserved. -
Smart Mobile Device to Trace Moving Rogue Objects in Smart City Utilizing Dynamic Source Dynamic Destination Tracking Algorithm
In the present literature, various algorithms are available for computing the shortest path between two objects. The maximum number of these algorithms compute the shortest path either between two static objects or one static object and one dynamic object. This article presents an insight to integrated Mobile Edge Computing (MEC) based smart devices for tracking mobile rogue objects based on dynamic source and dynamic destination optimal cost estimation. This device considers any two mobile objects to estimate the shortest path between them. The proposed Ant Colony Optimization (ACO) based algorithm considers the property of dead-end removal and nth path exploration with efficient self-loop removal strategy. To review the performance of the proposed algorithm, experimentations are carried out and compared with several well-established shortest cost estimation techniques available in the literatureFloyd Warshall, Bellman Ford, Dijkstra, A* algorithms and the only dynamic shortest path algorithm. The detailed algorithmic comparisons clearly indicate the superiority of the proposed one over the existing dynamic and present state-of-the-art shortest path estimation methodologies. 2023 IETE. -
Smart Online Oxygen Supply Management though Internet of Things (IoT)
We are surrounded by oxygen in the air we We cannot even exist without the ability to breathe. The need for oxygen has increased during the COVID19 pandemic, and although there is enough oxygen in our country, the main issue is getting it to hospitals or those in need on time. This is simply due to a significant communication gap between suppliers and hospitals, so we plan to implement an idea that will close this gap using real-time tracking as we can track the movement of oxygen tankers by gathering the requirements. We are using an ESP32 Wi-Fi module, a MEMS pressure sensor that enables the combination of precise sensors, potential processing, and wireless communication, such as Wi-Fi, Bluetooth, IFTTT, and MQTT protocols, to implement it successfully. The pressure sensor publishes the value of oxygen remaining from the location to the MQTT broker. 2022 IEEE. -
Smart People Counting System by Enhancing Accuracy and Affordability with YOLOv5 and Cloud-Based Integration
Considering that all moving objects are humans, much of the work in data is based on recognizing and tracking moving objects. In this work, we present a method for counting peoples faces. Even though we use the face mask, the deep learning-based YOLOv5 algorithm and Faster R-CNN allow us to recognize the face. We do a very good job of counting people. To make the calculation more accurate, we introduced a new type of intelligent small scale computing system consisting of cheaper hardware and user-friendly cloud computing software. These findings show that intelligent computing systems can realize human vision. Additionally, by combining inexpensive hardware with cloud-based software, the planning process becomes more transparent and cost-effective. Finally, the web application allows users to view the number of authorized and unauthorized users. Based on the results obtained from this method, the deep learning YOLOv5 algorithm is used to identify and match human images to increase security, and thanks to cloud storage, users can easily view all calculated results, increasing the accuracy by 98.53%. Owing to the truth that most of the secure watches cannot be able to check each and each individual The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Smart Phone based Fundus Imaging for Diabetic Retinopathy Detection
INTRODUCTION: Diabetic retinopathy (DR) is one of the consequences of diabetes which if untreated may lead to loss of vision. Generally, for DR detection, retinal images are obtained using a traditional fundus camera. A recent trend in the acquisition of eye fundus images is the usage of smartphones to acquire images. OBJECTIVES: This paper focuses on the study of existing works which incorporated smartphones for obtaining fundus images and various devices available in the market. Also, the common datasets used for carrying out DR detection using smartphone-based fundus images as well as the classification models used for the diagnosis of DR are explored. METHODS: A search of information was carried out on articles based on DR detection from fundus images published in the state-of-the-art literatures. RESULTS: Majority of the works uses SBFI devices like 20D lens, EyeExaminer etc. to obtain fundus image. The common databases used for the study are EyePACS, Messidor, etc. and the classification models mostly rely on deep learning frameworks. CONCLUSION: The use of smartphones for capturing fundus images for DR detection are explored. Smartphone devices, datasets used for the study and currently available classification models for SBFI based DR detection are discussed in detail. This paper portrays various approaches currently being employed in SBFI based DR detection. 2023 A. Benjamin et al. -
Smart pollution monitoring system
The world has travelled a long way through the industrial revolution. One of the consequences that the industries and its different forms gave to humanity is pollution. The environment that we live is being polluted in different ways. Different parts of the world are already experiencing air pollution as a matter of concern. The increasing amount of industries and the emission of gas by the vehicles cause much damage to the air. We are in a situation where we need to monitor the amount of pollution in our areas of living and working. In order to monitor pollution, the paper proposes an efficient and low-cost method with the help of the internet of things (IoT). The system is designed to monitor the levels of CO, CO2, smoke, alcohol, NH3, temperature and humidity. The various alarms and notification are arranged in such a way that the information is given when there is any sign of threat. The remote monitoring is made possible with dedicated website and mobile app. BEIESP. -
Smart Portable Neonatal Intensive Care for Rural Regions
Every year, an increasingly large number of neonatal deaths occur in India. Premature birth and asphyxia are being two of the leading causes of these neonatal deaths. A well-regulated thermal environment is critical for neonatal survival. In the current scenario, it is impossible for the health centers in the rural areas of India to afford a neonatal incubator for every newborn due to its price and transportability. The successful delivery of neonates is hampered in India due to its increasing population along with limited technology and resources. Thus, a prototype of an incubator has been designed that is affordable, transportable, and energy saving for the health centers in the rural regions, with an AI-based decision support system. Springer Nature Singapore Pte Ltd 2020. -
Smart Precision Irrigation Techniques Using Wireless Underground Sensors in Wireless Sensors
The term brilliant accuracy agribusiness alludes to advances like the Internet of Things, remote sensors, and artificial reasoning on the ranch. A definitive objective of this paper is to expand the quality and amount of the harvests while advancing the human work utilized, use of water system, and diminishing the water system times in light of climate forecast. This proposed framework utilizes the three kinds of sensors like Moisture sensor is used to detect the dirt dampness, the Humidity sensor is utilized to return how much water is present in the encompassing air, Temperature sensors are utilized to give the temperature of the dirt. Each of the three qualities is passed to the remote sensor hub and moved to the information lumberjacks. At long last, the information lumberjack will send the message like beginning the water system to a programmed water lock framework. When all water measures arrive at the water system limit, the programmed water lock framework will be shut. By using the underground, remote sensors, we can track the conditions of various agricultural applications such as soil properties, seed varieties and monitor the environmental situations. Every gadget contains significant gear like sensors, memory, a processor, and a power source. 2022 IEEE. -
Smart Product Packing and IoT Marketing: Enhancing Customer Interaction
The convergence of smart product packaging and IoT marketing has transformed commerce. This study examines the fundamental ramifications of convergence and its potential to improve customer engagement. Our research shows the transformational potential of these technologies via quantitative and qualitative analyses.Smart packaging outperforms non-smart items, giving firms an advantage, according to quantitative data. Regression and correlation analysis confirm IoT data-customer interaction. Our study also emphasizes ethical data acquisition, which supports data privacy and consumer protection.Consumers may expect personalized experiences, transparency, and real-time feedback from this technology transformation. Smart product packaging and IoT marketing enable readers to make educated decisions and influence product development to meet changing consumer expectations.This research allows academics to study the ideas and models that affect consumer engagement. Data privacy and consumer protection may inform IoT marketing and smart device packaging policy.Our research guides organizations and customers towards better customer interactions, data-driven decision-making, and ethical data practices in this changing age. The future promises revolutionary customer contact. 2023 IEEE. -
Smart production monitoring using drones in cyber-physical agricultural systems
The population of the world has shown a notable swift in recent years and the need for food has also gradually increased. The extra demand could be met by smart agricultural systems because manual and traditional crop cultivation is tedious, time-consuming and requires manpower to a great extent. The increased population is not the only factor for the shortage of food; there are many other influencing factors involving crop damage due to insects, lack of monitoring, and many others that should be overcome by the implementation of smart technologies in agriculture and resulting in a revolution of the agriculture or it can be addressed as Agri 4.0. This chapter provides insight into the implementation of drone technology which will result in many positive shifts in Agri 4.0. To address the various associated problems, causes, and consequences in the production, the smart production system with the incorporating technologies shows the notable solutions. Through the underlying chapter, the need, usage, architecture, implementation, and other related aspects are discussed. 2024 Elsevier Inc. All rights reserved. -
Smart Satellites: Unveiling the Power of Artificial Intelligence in Space Communication-A Study
The incorporation of Artificial Intelligence (AI) into space and satellite communication represents a paradigm shift in the way we explore, navigate, and communicate beyond our planet. This article is about the impact of AI on satellite operations, and the broader field of its communication to the earth. The article explores how AI enhances spacecraft autonomy, mitigates signal degradation, and improves the overall reliability of communication performance Satellite communication benefits from AI-driven advancements, in the areas of signal processing and optimization. Furthermore, examines the integration of AI in space-based challenges and opportunities associated with large-scale satellite networks. AI playing a crucial role in detecting and mitigating cyber security threats in space communication systems. This paper comes up with the perception into the future trends and potential advancements in AI applications for space and satellite communication. 2024 IEEE. -
Smart Sensory Approach for Soil Health Tracking based Precision Farming
Internet of Things (IoT) technology will have an impact on every area in the future as it will make everything intelligent, which will affect everyone's daily lives. It is a network composed of many devices that can configure themselves. The use of IoT in smart farming is transforming traditional agricultural practices by reducing crop loss, improving them, and making them more cost-effective for farmers. The study's goal is to propose a technological model for soil health monitoring that uses smart sensors and intelligent methods to communicate with farmers through a variety of channels. Farmers will benefit from the real-time farm data (temperature, humidity, soil moisture, UV index, and IR) that allows them to practice smart farming while increasing crop yields and conserving resources. 2023 IEEE. -
Smart Skin Cancer Diagnosis: Integrating SCA-RELM Method for Enhanced Accuracy
One out of three cancers now is skin cancer, a figure that has exploded in the previous several decades. Melanoma is the worst kind of skin cancer and occurs in 4% of cases. It is also the most aggressive type. The health and economic impact of skin cancer is substantial, especially given its rising incidence and fatality rates. However, with early detection and treatment, the 5-year survival rate for skin cancer patients is much improved. As a result, a lot of money has gone into studying the disease and developing methods for early diagnosis in the hopes of stopping the rising tide of cancer cases and deaths, particularly melanoma. In order to enhance non-invasive skin cancer diagnosis, this research examines a range of optical modalities that have been utilized in recent years. The suggested system uses image processing to identify, remove, and categorize lesions from dermoscopy images; this system will greatly aid in the detection of melanoma, a type of skin cancer. A median filter is employed for preprocessing. Using watershed and clever edge detector, it can segment objects. The BOF plus SURF method is employed for feature extraction. It employs SCA-RELM, which performs better than the other two conventional approaches, to train the model. 2024 IEEE. -
Smart songs selection in playlists using parallel k-means clustering
Most songs today are of different tempo, pitch and time signature. In a music player application, the typical shuffle picks the succeeding song or preceding song at random with no parameters to choose the songs. Different songs from different genres can have a tempo range anywhere between forty beats per minute and three hundred beats per minute. In this paper, the quick and efficient parallel k means clustering algorithm is implemented in Hadoop on the million-song dataset subset to form clusters for the songs based on tempo and pitch. The aim of this paper is to reduce the variation that occurs when a typical shuffle picks the succeeding song at random. This variation can be in the form of tempo or other parameters. The formation of clusters and intern the reduction in the variation of tempo can be used in a new 'smart shuffle'. After the clusters have been formed, the smart shuffle picks the songs within that specific cluster. This paper aims at reducing the variation by 50%. This would have many musical benefits and would also be more pleasing to the listener. 2018 IAEME Publication. -
Smart Steering Wheel for Improving Drivers Safety Using Internet of Things
Nearly 3700 people every day die on the worlds roads in collisions with trucks, cars, buses, motorcycles, bicycles, or pedestrians.The cause of accidents is drowsiness, drunk driving, breaking the speed limit, Driver health issue and rash driving. The most concept of this venture is to avoid the street mishap so we are utilizing liquor location sensor, eye flicker sensor, over speed control sensor, temperature sensor, beat sensor. To detect drowsiness, speed of the vehicle, drivers health, alcohol consumed by the driver, and rash driving status the model is installed with sensors in steering wheel and camera. The sensors will detect the physical condition of the driver and the camera module will take the live recording of the drivers face part to detect the drowsiness. Simple but effective strategies are used to improve the baseline detection/tracking algorithm and the eye-state classification algorithm, and the results are tabulated to increase the systems dependability and accuracy. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.