Smart Wearable Gadget for Miners Using IOT

Safety is the most important part of any kind of assiduity is safety. In extreme circumstances, safety-related negligence could result in the destruction of expensive clothing or the loss of human life. Every min-ing diligence adhere to a few basic preventative measures in order to avoid any generally unwelcome wonders. The most important component at this time is communication in order to continuously monitor various pa-rameters and take the appropriate actions as a result to avoid any risks linked with the product or the management of mortal funds. A stable and wide-range effective communication system between personnel in the mine and the control centre must be built in order to increase safety in un-derground mines. The cable communication network technology is inef-fective within underground mines. Here we can tackle the matter of acci-dents which end with death of several people per annum. It is discovered that the speed of fatality within the coal pit industry is almost six times the speed for all private industries. And most of those accidents are because of toxic gases, fires, and a lack of rescue systems. By implementing mine surveillance gadgets, which may be used within the mine and detect the number of various gases, fall, emergency detection and report to them. This article focuses on the design and analysis of the smart wearable gadget for miners in the mining industry using IoT

IOT Based Smart Farming Application

Smart agriculture is one of the Internet of Things' most important uses. Water, fertilizer, and crop yield waste are all reduced via smart agriculture. The manual detection of specifications like temperature, moisture, and humidity in the existing agricultural system drives up labor costs, and continuous monitoring is not possible. The irrigation procedure is carried out automatically in this study utilizing various sensors, which reduces manual work. It is suggested to utilize a sensor-based monitoring system for crop fields. It would entail gathering information on the soil moisture, humidity, and temperature. Automation of irrigation is possible by keeping an eye on all these variables. Unquestionably, smart farming is a key facilitator in providing more food with less resources for a growing global population. While this is essential to feeding the world's expanding population responsibly, smart farming also offers producers and communities throughout the world additional advantages. Farmers may raise yields and improve environmental management by using these strategies. By monitoring the field, IoT-based smart agriculture enhances the overall farming system. The Internet of Things in agriculture helps farmers save time and lessen the usage of resources like water thanks to sensors and connections. electricity, internet-connected temperature monitoring

Identification of Phishing Attacks using Machine Learning Algorithm

Phishing is a particular type of cybercrime that allows criminals to trick people and steal crucial data. The phishing assault has developed into a more complex attack vector since the first instance was published in 1990. Phishing is currently one of the most prevalent types of online fraud behavior. Phishing is done using a number of methods, such as through emails, phone calls, instant chats, adverts, pop-up windows on websites, and DNS poisoning. Phishing attacks can cause their victims to suffer significant losses, including the loss of confidential information, identity theft, businesses, and state secrets. By examining current phishing practises and assessing the state of phishing, this article seeks to assess these attacks. This article offers a fresh, in-depth model of phishing that takes into account attack stages, different types of attackers, threats, targets, attack media, and attacking strategies. Here, we categorise websites as real or phishing websites using machine learning techniques including Random Forest, XGBoost, and Logistic Regression. Additionally, the proposed anatomy will aid readers in comprehending the lifespan of a phishing attack, raising awareness of these attacks and the strategies employed as well as aiding in the creation of a comprehensive anti-phishing system

IOT Based Real Time River Water Quality Monitoring and Control System

Water quality monitoring systems currently in use are manual and involve tedious processes that are time intensive. This research suggests a system with sensors for water quality monitoring. Access to real-time data may be obtained through remote monitoring and the Internet of Things. A wireless sensor network (WSN) contains a micro-controller for data processing, a mechanism for communicating between and inside nodes and many (IoT). Using Spark flow analysis with Spark MLlib, deep on it. The agent will receive a warning SMS automatically if the detected value exceeds the threshold. Our plan to develop a high- frequency, high-mobility, low-power water monitoring system makes it special. As a result, the Bangladeshi people will find our proposed approach highly useful in raising awareness of and putting an end to water pollution

Noise Level Notifier

This paper involves utilizing an Arduino Uno as the primary hardware to measure the sound level in a library. The amount of noise in the region is measured using a sound sensor. The sound sensor signals are amplified using the operational amplifier function of the integrated circuit LM 567. There are two types of output available: audio and visual. The audio output takes the form of a personalized message that is played over speakers. LEDs are employed to offer visual feedback, with white LEDs used in noise-free environments (sound level 45 dB, yellow LEDs used when sound levels are above 65 decibels, and red LEDs used when sound levels are significantly above 80 decibels). A TIP 220 transistor is used to amplify the signals. A TIP 220 transistor amplifies the signals to create an output for the speaker. There is an audio message that corresponds to each sound level

Multi-Parameter Sensor Based Automation Farming

IOT innovation is used in the development of the Smart Farming Tracking the System. An Arduino Uno, a temperature humidity sensor, soil moisture sensor, water level sensor, water pumps, and DC motors strength this system. If the smart farming tracking system turns on, the sensors find the field’s water level and the soil’s moisture level. If the irrigation water stage falls below the level defined for a specific crop grown in the growing area, the irrigation system is going to start to pump water. The IOT warns concerning current level of water, soil moisture stage, and motor beginning will be shown on the LCD panel of the section. We are able to use the pumps by hand via a webpage. The farmers are additionally getting this data via mobile phone. By hitting a system- provided link, the individual using it may firmly prevent the water’s flow within the field. While carried out, the system will assist landowners to preserve suitable soil water and moisture levels, thus boosting yields with little work. The goal of this article is to identify grow illnesses and reduce losses in money. For picture appeal, we suggested an entirely based on deep learning method. We put the three most common Neural Network Designs to the test: Faster Region-based entirely judgment (SVM)Support Vector Machine Region-based entirely (RF) Random Forest method. The method suggested in the research can correctly detect many types of disease and is capable of dealing in complicated situations. In addition, the method may be expanded to recommend fertilizer according to extent evaluation as well as measurement. artificial intelligence (AI) entirely Machine Learning Response to this the combination the issue is a supervised categorization judgment

Effects of slag content on the residual mechanical properties of ambient air-cured geopolymers exposed to elevated temperatures

This paper presents the effects of various slag contents on the residual compressive strength and physical properties of ambient air-cured fly ash-slag blended geopolymers after exposure to various elevated temperatures up to 800°C. The results showed an increasing trend in the compressive strength of ambient air-cured geopolymers with increase in the slag contents after exposure to 400 and 600°C temperatures. This trend deviated, however, at 800°C. Nevertheless, all the geopolymers showed reductions in control compressive strength at ambient temperature after exposure to elevated temperatures. The reductions were much higher at 600 and 800°C compared to 400°C. All the geopolymers exhibited significant damage in terms of cracking after exposure to a temperature of 800°C compared to 400 and 600°C and significant damage occurred at slag contents of 15–30%. Scanning electron microscopic (SEM) images of the above geopolymers also showed higher porosity at 800°C compared to 400 and 600°C. Traces of calcite/calcium silicate hydrate (CSH) peaks are observed in the X-ray diffraction (XRD) analysis of fly ash-slag geopolymers, and the intensity of those peaks increased with increases in slag contents. After exposure to elevated temperatures, the calcite/CSH peaks disappeared and new phases of nepheline and gehlenite were formed at 800°C in all the fly ash-slag geopolymers

IOT Based Smart Farming Application

Smart agriculture is one of the Internet of Things' most important uses. Water, fertilizer, and crop yield waste are all reduced via smart agriculture. The manual detection of specifications like temperature, moisture, and humidity in the existing agricultural system drives up labor costs, and continuous monitoring is not possible. The irrigation procedure is carried out automatically in this study utilizing various sensors, which reduces manual work. It is suggested to utilize a sensor-based monitoring system for crop fields. It would entail gathering information on the soil moisture, humidity, and temperature. Automation of irrigation is possible by keeping an eye on all these variables. Unquestionably, smart farming is a key facilitator in providing more food with less resources for a growing global population. While this is essential to feeding the world's expanding population responsibly, smart farming also offers producers and communities throughout the world additional advantages. Farmers may raise yields and improve environmental management by using these strategies. By monitoring the field, IoT-based smart agriculture enhances the overall farming system. The Internet of Things in agriculture helps farmers save time and lessen the usage of resources like water thanks to sensors and connections. electricity, internet-connected temperature monitoring