The dramatic advancments on communication and networking technologies have led to the emergence of Internet-of-Things (IoT). IoT technology has opened the door for various applications. In particular, the home automation was one of the common applications that took the advantage of IoT. Several research efforts have addressed the home automation system using IoT covering wide range of functionalities. One of the concerning tasks is providing a secure system that can give alarms for suspicious activities within the house. This paper presents a secure house system based on IoT where several activities are being sensed and detected. Specifically, gas, humidity, body temperature and motion have been considered within the sensing based on two main types of micro-controller including Arduino and Raspberry Pi. Consequentially, an Android prototype has bene developed in order to give an interactive interface for warning the house owner regarding any suscpicious activities. Results of simulation demonstrated the efficancy of the proposed system
The importance of preserving the environment from waste and its pollution lies in many matters such as preserving people health, enhancing the aesthetic character of cites, attracting tourists, and protecting society from environmental disasters. The environmental wastes are the main dilemmas in our daily life and in the world at large. With the existence of modern technology, development and the field of the internet, many solutions have been undertaken to get rid these dilemmas. In this paper, a smart waste system based on internet of things (IoT) technique has been proposed using ESP-32 Wi-Fi microcontroller. This system can be adopted to avoid the accumulation of waste in the streets that distort the face of civilization, also to reduce the burden of workers and limit the workforce. The system is based on a multiple sensors in the garbage baskets, as they measure the waste level by using ultrasonic sensor, the moisture percent and temperature degree using DHT-22 sensor. The sensors data are processed by ESP32 microcontroller and displayed to both LCD screen using I2C protocol and mobile application using IoT cloud. System baskets automatically open their covers when the person approaches with a distance less or equal to 30 cm to throw garbage. Any approval waste basket is automatically discharged through an underground dump system using conveyor belt if the basket is full by 80% garbage and/or the basket moisture reaches to 40%.
With the dramatic evolution in networks nowadays, an equivalent growth of challenges has been depicted toward implementing and deployment of such networks. One of the serious challenges is the security where wide range of attacks would threat these networks. Denial-of-Service (DoS) is one of the common attacks that targets several types of networks in which a huge amount of information is being flooded into a specific server for the purpose of turning of such server. Many research studies have examined the simulation of networks in order to observe the behavior of DoS. However, the variety of its types hinders the process of configuring the DoS attacks. In particular, the Distributed DoS (DDoS) is considered to be the most challenging threat to various networks. Hence, this paper aims to accommodate a comprehensive simulation in order to figure out and detect DDoS attacks. Using the well-known simulator technique of NS-2, the experiments showed that different types of DDoS have been characterized, examined and detected. This implies the efficacy of the comprehensive simulation proposed by this study.
Healthcare monitoring is a field that caught many researchers from the computer science community in the last decade. In the literature, various levels of people have been considered when proposing a health monitoring system. However, some aspects are still not adequately tackled such as monitoring workers’ health status within confined space where workers would be located in underground environment with less oxygen and a lot of dust. This paper proposes an IoT health monitor system for worker in confined places. The proposed system utilizes four types of microcontroller sensors including LM35 for measuring body temperature, heart beat rate sensor, blood pressure sensor and LPG gas sensor. All the aforementioned sensors are being connected via a GPS module in order to transmit the readings into a smartphone application. A simulation has been conducted to test the proposed sensors where competitive commercial measures have been used as a benchmark. Result of simulation showed that the sensors have fair accuracy that is near-identical to the benchmark.
In Statistical Process Control, many techniques exist for monitoring the stability of a process over time. In this work, we study the relationship of the response variable with explanatory variables in the form of linear profiles for detecting changes in slope and intercept of the linear quality profiles. We used the transformation of explanatory variables approach used for make the regression estimates independent of each other to have zero average. A comparative study of three phase-II methods using DEWMA statistics in monitoring and capturing undesirable deviations in the slope, intercept, and variability is also studied by applying different proposed run rules schemes i.e., R1/1, R2/3, R3/3. Monte Carlo simulations were carried out on R-Software for finding the results of proposed schemes by taking various levels of shifts for intercept, slope, and standard deviation in identifying the false alarm rate of a process. The simulation results based on the average run length criterion show that the proposed run rule schemes improve the detection ability of the control structure. Among all the proposed schemes R2/3 is found to be the best one because of its quick detection ability of false alarm rate. The proposed scheme also shows superiority in comparison to other schemes. The simulation results are further justified with a real data application.
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