Performance evaluation of LoRa based sensor node and gateway architecture for oil pipeline management

These days, the oil industrial industry is leaning toward employing smart field improvements to streamline various activities in the midstream area. Oil transportation over large distances via pipelines has a cheap cost and high efficiency in this sector. If pipelines are not properly maintained, they may fail, potentially causing catastrophic, long-term, and irreversible consequences on both natural and human conditions. Low power wide area networks (LPWANs) are without a doubt one of the domains that cause the most from industrial fields when it comes to realizing the vision of the internet of things (IoT). Long-range (LoRa) is an emerging LPWAN technology that is particularly useful for transmitting data over long distances. The goal of this work is to offer a methodology for managing oil pipelines over long distances utilizing the LoRa communication protocol and the installation of sensor nodes and LoRa gateways along the pipeline. We also used the optimized network engineering tools (OPNET) simulator to examine various simulation findings of LoRa performance

Development in building fire detection and evacuation system-a comprehensive review

Fire is both beneficial to man and his environment as well as destructive and deadly among all the natural disasters. A fire Accident occurs very rarely, but once it crops up its consequences will be devastating. The early detection of fire will help to avoid further consequences and saves the life of people. During the fire accidents, it is also important to guide people within the building to exit safely. Because of this, the paper gives a review of literature related to recent advancements in building fire detection and emergency evacuation system. It is intended to provide details about fire simulation tools with features, suitable hardware, communication methods, and effective user interface

Review of the State of the Art of Transfer Learning for Plant Leaf Diseases Detection

Plant leaf diseases can have a significantly negative influence on the quantity and quality of agricultural cultivation, as well as the safety of food production. Plant leaf diseases could potentially entirely prevent the harvest of grains in some situations. Therefore, it is extremely important from a pragmatic standpoint to look for quick, automatic, cheap, and accurate ways to detect plant leaf diseases. One of the well-known plant leaf disease detection approaches is deep learning. Deep learning has several drawbacks as a result of the huge amount of data required to train the network. When a dataset has inadequate photographs, performance falls. An approach called "Transfer Learning" is an extensively used method for addressing the shortcomings of a small dataset, the length of the training process, and improving the performance of the model. In this study, we investigated transfer learning for deep CNNs to improve the learning capability to recognize leaf disease. This survey focuses on categorizing and analyzing the recent developments in transfer learning for Deep CNN situations to enhance learning performance by reducing the need for extensive training data collecting

A reliable approach to customizing linux kernel using custom build tool-chain for ARM architecture and application to agriculture

ARM processors are receiving more attention as per IoT customized devices are concerned. A novel framework design tool for Linux kernel customization on ARM architecture has been illustrated. The tool is best suit from ARM based platformss like Raspberry pi, Beagle Bone, Intel Edison etc. The proposed techniques uses different tool chains for the kernel customization. The paper represents an integral framework that integrates all the cross compiling tools and simplifies the overall process. The framework has been used for the development of a customized kernel for Raspberry Pi on Ubuntu 14.04 host computer. The custom kernel has been ported in to Raspberry Pi and the performance evaluation has been done. Furthermore, the analysis aims to help users choose and configure their tracers based on their specific requirements to reduce their overhead and get the most of out of them. The testing of customized OS with raspberry Pi device in the field of agriculture. The smart node/mote is designed based on it to deploy in the agriculture field to test its feasibility. The group of nodes data is gathered using ThingSpeak cloud server. The gathered sensory data is analyzed and forecast on farmer’s mobile phone in the form of APP or handheld device for farmer

Role of Digitalization in Election Voting Through Industry 4.0 Enabling Technologies

The election voting system is one of the essential pillars of democracy to elect the representative for ruling the country. In the election voting system, there are multiple areas such as detection of fake voters, illegal activities for fake voting, booth capturing, ballot monitoring, etc., in which Industry 4.0 can be adopted for the application of real-time monitoring, intelligent detection, enhancing security and transparency of voting and other data during the voting. According to previous research, there are no studies that have presented the significance of industry 4.0 technologies for improving the electronic voting system from a sustainability standpoint. To overcome the research gap, this study aims to present literature about Industry 4.0 technologies on the election voting system. We examined individual industry enabling technologies such as blockchain, artificial intelligence (AI), cloud computing, and the Internet of Things (IoT) that have the potential to strengthen the infrastructure of the election voting system. Based upon the analysis, the study has discussed and recommended suggestions for the future scope such as: IoT and cloud computing-based automatic systems for the detection of fake voters and updating voter attendance after the verification of the voter identity; AI-based illegal, and fake voting activities detection through vision node; blockchain-inspired system for the data integrity in between voter and election commission and robotic assistance system for guiding the voter and also for detecting disputes in the premises of election booth

An internet of things enabled framework to monitor the lifecycle of Cordyceps sinensis mushrooms

Cordyceps sinensis is an edible mushroom found in high quantities in the regions of the Himalayas and widely considered in traditional systems of medicine. It is a non-toxic remedy mushroom and has a high measure of clinical medical benefits including cancer restraint, high blood pressure, diabetes, asthma, depression, fatigue, immune disorder, and many infections of the upper respiratory tract. The cultivation of this kind of mushroom is limited to the region of the Sikkim and to cultivate in the other regions of the country, they are need of investigation and prediction of cordyceps sinensis mushroom lifecycle. From the studies, it is concluded that the precision-based agriculture techniques are limitedly explored for the prediction and growth of Cordyceps sinensis mushrooms. In this study, an internet of things (IoT) inspired framework is proposed to predict the lifecycle of Cordyceps sinensis mushrooms and also provide alternate substrate to cultivate Cordyceps sinensis mushrooms in other parts of the country. As a part of lifecycle prediction, a framework is proposed in this study. According to the findings, an IoT sensor-based system with the ideal moisture level of the mushroom rack is required for the growth of Cordyceps sinensis mushrooms

Role of Blockchain Technology Integration for Green Bonds Issuance with Sustainability Aspect

Green bonds have gained significant attention in supporting sustainable development goals for achieving sustainability. During the issuance of green bonds, there are a few concerns such as standardization, greenwashing, and lack of benefits that can be gained with green bonds. However, blockchain technology is a promising solution for green bond issuance because it has already shown its impact on different finance activities. This study aims to address and analyze the role and significance of green bond issuance for meeting sustainability with blockchain technology and also suggested recommendations for future research. Decentralized application based on the Algorand blockchain and high-level architecture proposed for the issuance of green bonds is at the primary level. There is no discussion regarding standardizing the environmental data, and the number of benefits gained by the green bond is not addressed in the previously published literature. From the analysis, it has been identified that a similar framework of blockchain cannot be implemented as the geographical and environmental parameters are quite different for every nation. So, every nation needs to customize the framework according to the nation's requirements. This study is the first attempt to combine information from previously published research about green bond issuance and integration of blockchain for green bond issuance, enlightening the disruption caused in the issuance of green

Energy Efficient RF Remote Control for Dimming the Household Applainces

During recent years there is a strong trend towards radio frequency (RF) remote controls as it is delivering even more comfort to the users and increased usability with high robustness of the RF links. Lower power consumption with new features and security make RF remote control systems more competitive with widely used IR remote control systems.  In this paper we propose, a RF module based real time system, which is an integrated system designed to control the dimming or speed of the appliances. Zigbee module is used as RF module to establish wireless link between Remote and appliance section having 9600kbs baud rate and range of 100m. Dimming control circuits is part of appliances section which is used to control the appliances corresponding to signals generated by the remote section. This system provides energy efficient solution for household uses. DOI: http://dx.doi.org/10.11591/telkomnika.v13i2.7046

Arduino-Based embedded systems: interfacing, simulation, and LabVIEW GUI

Arduino is an open-source electronics platform based on easy-to-use hardware and software while LabVIEW is a graphical programming telling how to connect functions and work with a variety of datatypes when constructing applications.This book will help beginners to get started with Arduino-based embedded systems including essential know-how of the programming and interfacing of the devices. Book includes programming and simulation of Arduino-based projects and interfacing with LabVIEW, based on practical case studies. The book comprises of total twenty five chapters with description, working model of LabVIEW and programming with Arduino IDE