The paper provides the overview benefits of applying nanotechnology in various fields, giving an update on the state of nanotechnology breakthroughs in electronics and communication engineering. This paper offers an overview of some of the most current developments in nanotechnology, encompassing a range of gadgets such as tiny transistors, paper batteries, robotics, networks, and wireless technologies. For this reason, it is anticipated that nanotechnology will make it possible to produce increasingly efficient, powerful, yet smaller and less expensive gadgets.

Electronic technology, a relatively recent production technology in engineering, has the potential to optimize and improve the labor-intensive and complex manufacturing process of the past, thereby decreasing labor and resources and increasing productivity. As electronic technology continues to advance, it has progressively emerged as a key technological component of the automotive, engineering, and industrial sectors and has created favorable development circumstances for India’s industrial revolution. The application and development prospects of electronic technology benefits in the engineering area were thoroughly examined and discussed in this study, which also offered some recommendations for the technology's future development and application prospects. Due to the rapid growth of network technology and the emergence of new categories with the information age, electronic technology has become widely used in many different industries. This study examines the state of electronic technology development in our nation and discusses the future direction of this fields development. It primarily investigates the electronic technologies used in each industry. The electronic technology is a significant component of many industries and is intimately linked to our daily lives. As a result, it is currently developing in an intelligent, digital, user-friendly, integrated direction. More broadly, its application in human life necessitates a combination of this development trend and ongoing innovation and development to meet the needs of the populace. Currently, electronic technology is a significant technological revolution that has drawn attention and worry due to its growing potential worth. As a result, it needs to be founded on a favorable attitude toward the advancement of electronic technology, support the study of the theory and practice of investing in electronic technology. Major Findings: One important area of electronic technology; innovation is the development of common goals between various domains. New technologies are always evolving, which not only makes them better but also leads to the creation of products with more features. Rapid advancements in modular technology and high frequency switching power supply will propel all of electronic technology, enhancing the integration of high quality and high efficiency power. Therefore, electronic technology must constantly change to meet people's evolving wants. It is currently evolving in an intelligent, digital, integrated, and user-friendly manner as a result.

The manufacturing industry is growing quickly, which has led to an investigation into the possibilities of Internet of Things and wireless sensor networks, which will increase production efficiency. Since the Industrial Revolution, the manufacturing sector has played a significant role in both company and national economies. One of the most important issues in the current era of Industrial Revolution 4.0 is cyber-integrated manufacturing. IoT-enabled smart manufacturing enables an interactive relationship between smart machines to exchange data and information, which is essential for complex systems to make decisions about the working environment in real time. Increasing resource and energy efficiency is the most crucial step towards achieving manufacturing sustainability on a daily basis. Business organizations nowadays face several challenges as a result of fast technology innovation and intense global rivalry. To overcome these issues and advance sustainable growth, they must innovate their procedures and goods. IoT was adopted by industries in a number of areas, from raw material purchases to customer support and service. The Industrial Revolution 4.0 is thought to have heavily relied on the Internet of Things, which presents a potential opportunity to develop manufacturing-related services and applications. Furthermore, it facilitates the interactive exchange of data and information amongst smart devices, which is necessary for complex systems to make decisions about their real-time working environments. Major Findings: IoT is a cutting-edge technology that greatly enhances the manufacturing industry. It enabled smart manufacturing which promotes an interactive relationship between smart machines to exchange data and information, allowing complex systems to make judgments about the real-time working environment.

In artificial intelligence (AI), computer vision consists of intelligent models to interpret and recognize the visual world, similar to human vision. This technology relies on a synergy of extensive data and human expertise, meticulously structured to yield accurate results. Tackling the intricate task of locating and resolving blockages within sewer systems is a significant challenge due to their diverse nature and lack of robust technique. This research utilizes the previously introduced “S-BIRD” dataset, a collection of frames depicting sewer blockages, as the foundational training data for a deep neural network model. To enhance the model’s performance and attain optimal results, transfer learning and fine-tuning techniques are strategically implemented on the YOLOv5 architecture, using the corresponding dataset. The outcomes of the trained model exhibit a remarkable accuracy rate in sewer blockage detection, thereby boosting the reliability and efficacy of the associated robotic framework for proficient removal of various blockages. Particularly noteworthy is the achieved mean average precision (mAP) score of 96.30% at a confidence threshold of 0.5, maintaining a consistently high-performance level of 79.20% across Intersection over Union (IoU) thresholds ranging from 0.5 to 0.95. It is expected that this work contributes to advancing the applications of AI-driven solutions for modern urban sanitation systems.

There is an increasing trend of using automated and robotic systems for the tasks that are hazardous or inconvenient and dirty for humans. Sewers maintenance and cleaning is such a task where robots are already being used for inspection of underground pipes for blockages and damage. This paper reviews the existing robotic systems and various platforms and algorithms along with their capabilities and limitations being discussed. A typical mid-size city in a developing country, Pune, India is selected in order to understand the concerns and identify the requirements for developing robotic systems for the same. It is found that major concern of sewers are blockages but there is not enough information on both real-time detection and removal of it with robotic systems. On-board processing with computer vision algorithms has not been efficiently utilized in terms of performance and determinations for real-world implementations of sewer robotic systems. The review highlights the available methodologies that can be utilized in developing sewer inspection and cleaning robotic systems.

Online handwritten character recognition is having wide areas of application in real life environment. Therefore the accuracy of such systems should be more, efficient and faster to process applications. A lots of research work is still going on over handwritten character recognition based on different languages and scripts. For any handwritten character recognition, there are three main tasks such as Image segmentation, Feature Extraction and Classification. Feature extraction is a very essential step for online handwritten character recognition. As the success rate of a recognition system is often depends on a good feature extraction method. The feature extractor determines which properties of the preprocessed data are most significant and should be used in further stages. In this paper different feature extraction methods are discussed and presented related with Devnagari script and proposed efficient and optimized extraction method with their comparative analysis. The accuracy of recognition system is majorly depending on feature extraction phase, types of features and size of features. The hybrid efficient, faster and optimized feature vector is used which is combination of geometrical features, regional features, distance transform and gradient features. Feature vector length is 91. In addition to this, in existing cases, the time required for extracting the geometrical features is very high; however Universe of discourse is used to speed up the retrieval. From practical analysis, accuracy of proposed feature vector set is improved as compared to existing feature vectors.