An Overview of Neodymium Magnets over Normal Magnets for the Generation of Energy

Neodymium (NdFeB) magnets have become widely available in recent years and have replaced other types of magnet in many applications in modern products that require strong permanent magnets, such as motors in cordless tools, hard disk drives and magnetic fasteners. These magnets can be used to invent a new method of energy generation by using the magnetic field of magnet and convert the magnetic energy into kinetic energy without using any kind of fuel and overcoming the energy generation problem such as building a magnetic turbine. The main objective of the study was to study about the advantage of using NdFeB magnets over other magnets, nature of different type of neodymium magnets and how it can be used to convert magnetic energy into kinetic energy

Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.Comment: 14 Pages, 9 Figure

Bibliometric Review on Inertial Sensors based Position Estimation using Sensor Fusion

Background: This paper analyzes the position estimation of UAV in a 3D environment, on the basis of inertial sensors and sensor fusion algorithm, done from the year 1994 to 2020. This paper contains various bibliometric analyses previously done on this topic. Methods: The content for this topic was taken from the popular Scopus database. The Scopus provides many filters for searching databases with different document categories like document by year, country, etc. The research carried in this paper also includes co-authorship, citation analysis, etc. Results: A total of 345 articles were obtained from the last 20 years, on the topic of position estimation using inertial sensors based on sensor fusion. After analyzing this, it was concluded that the maximum amount of research was done in the year 2020 and it was seen that the contribution from china is maximum on this topic. The research is also increasing year by year. Conclusions: Out of 345 articles the English language has the largest number of articles on the position estimation of UAV in a 3D environment. From the analysis of it, it was seen that the number of articles was increased drastically in recent years; it was mostly due to the advancement in algorithms. This was clearly indicating that soon more advanced algorithms will come, which will provide a lot of scope for further research

Energizing the Future with Memories of the Past: The Wadas of Pune City

Pune, described as the Queen of the Deccan, [1] is located in the state of Maharashtra, India. It is a historic city associated with the Maratha Empire and seat of the Peshwa power. During the Colonial Period it was a British cantonment. Contemporary Pune city is considered as the cultural capital of Maharashtra and is also referred to as the Oxford of the East due to the presence of several well-known educational institutions. The old city of Pune is constituted by the seventeen Peths or localities. The wadas are a characteristic built-form that evolved during the Maratha Period. They were the residences not only of the Peshwas but also those connected with the administrative system of the times and are the manifestations of the culture of the period. They vary considerably in size and form. They have a characteristic spatial organization harmonizing form and space with distinct architectural features. They were once the seat of power, intrigue and grandeur. Now, they are the surviving witnesses of battle plans and palace intrigues at the height of glory of the Maratha Empire. After more than three hundred and fifty years the wadas themselves are waging a final battle for survival considering the apathy towards their woes and issues from both the civic body as well as their private owners. The objective of the paper is to explore the possibility of developing selected wadas as nodes in developing Pune city’s culture infrastructure as well as heritage showcase. It seeks site specific solutions of ‘Energizing the Future with the Memories of the Past’ in Pune city

Multiple Model Adaptive Complementary Filter for Attitude Estimation

Attitude estimation plays a major role in the autonomy of unmanned aerial vehicles and requires fusion of different sensor measurements. This paper describes an adaptive estimation scheme in which the weight parameter for the complementary filter (CF) is varied over time. The adaptive mechanism proposed here is inspired from the multiple model adaptive estimation (MMAE) scheme used for varying noise parameters in the Kalman filter structure. In this paper, the linear complementary filters are used as elementary blocks in the MMAE structure and their weights are modified probabilistically to obtain an accurate orientation estimate. It avoids the problem of manual selection of weight factor for complementary filter and provides a robust orientation estimate against varying system dynamics. The proposed MMAE based adaptive CF scheme is modular in nature and is dependent on the residual error between estimated and the measured orientation angle. It is applied on the real world datasets logged from inertial sensors and the performance of MMAE based CF structure is found to work promisingly as compared to the non-linear complementary filter versions and the extended Kalman filter framework

MultimodalGasData: Multimodal Dataset for Gas Detection and Classification

The detection of gas leakages is a crucial aspect to be considered in the chemical industries, coal mines, home applications, etc. Early detection and identification of the type of gas is required to avoid damage to human lives and the environment. The MultimodalGasData presented in this paper is a novel collection of simultaneous data samples taken using seven different gas-detecting sensors and a thermal imaging camera. The low-cost sensors are generally less sensitive and less reliable; hence, they are unable to detect the gases from a longer distance. A thermal camera that can sense the temperature changes is also used while collecting the present multimodal dataset to overcome the drawback of using only the sensors for detecting gases. This multimodal dataset has a total of 6400 samples, including 1600 samples per class for smoke, perfume, a mixture of smoke and perfume, and a neutral environment. The dataset is helpful for the researchers and system developers to develop and train the state-of-the-art artificial intelligence models and systems

MultimodalGasData: Multimodal Dataset for Gas Detection and Classification

The detection of gas leakages is a crucial aspect to be considered in the chemical industries, coal mines, home applications, etc. Early detection and identification of the type of gas is required to avoid damage to human lives and the environment. The MultimodalGasData presented in this paper is a novel collection of simultaneous data samples taken using seven different gas-detecting sensors and a thermal imaging camera. The low-cost sensors are generally less sensitive and less reliable; hence, they are unable to detect the gases from a longer distance. A thermal camera that can sense the temperature changes is also used while collecting the present multimodal dataset to overcome the drawback of using only the sensors for detecting gases. This multimodal dataset has a total of 6400 samples, including 1600 samples per class for smoke, perfume, a mixture of smoke and perfume, and a neutral environment. The dataset is helpful for the researchers and system developers to develop and train the state-of-the-art artificial intelligence models and systems

Bibliometric Review on IoT Based System for Remote Downloading on Microcontroller

Working with sensors has become an area of expertise within the domain of electronic engineering. On a day to day basis, thousands of sensors are put to use around us, for instance, in smoke alarms, speedometers, motors, computers, radiators etc. to accumulate sensor data, cables that connect the sensors to the bottom station after which the information is worked on. But cabling is often expensive especially when handling large scale industrial applications [5]. For an equivalent reason, low-cost wireless networks came into the picture recently and are in high demand. A research paper we found during our review of literatures, explores using raspberry pi type of a server to which other devices are going to be connected which will copy, store, and delete the file on the network itself. For this review, we went through papers that discussed and researched on the subject of downloading programs wirelessly on a microcontroller through a cloud-based system. The advantage of using cloud computing for IoT based applications increases the likelihood of, more devices joining the network. This makes it easier for IoT systems to grow efficiently thanks to reduced bandwidth and storage among other parameters [9]. We found some informative papers on sources such as, Google Scholar and Scopus that mention the MQTT protocol. The survey was conducted using the keywords mentioned below credited by various authors and publications from different countries. We gave more importance to the papers that were cited more often and also administered statistical analysis on the sources of the documents