A review of smart home applications based on Internet of Things

In this review paper, we have discussed the existing state-of-the-art practices of improved intelligent features, controlling parameters and Internet of things (IoT) infrastructure required for smart building. The main focus is on sensing, controlling the IoT infrastructure which enables the cloud clients to use a virtual sensing infrastructure using communication protocols. The following are some of the intelligent features that usually make building smart such as privacy and security, network architecture, health services, sensors for sensing, safety, and overall management in smart buildings. As we know, the Internet of Things (IoT) describes the ability to connect and control the appliances through the network in smart buildings. The development of sensing technology, control techniques, and IoT infrastructure give rise to a smart building more efficient. Therefore, the new and problematic innovation of smart buildings in the context of IoT is to a great extent and scattered. The conducted review organized in a scientific manner for future research direction which presents the existing challenges, and drawbacks.

Sensing, Controlling, and IoT Infrastructure in Smart Building: A Review

In this era of digitization and automation, the life of human beings is getting simpler as almost everything is automatic, replacing the old manual systems. Nowadays humans have made internet an integral part of their everyday life without which they are helpless. Internet of things (iot) provides a platform that allows devices to connect, sensed and controlled remotely across a network infrastructure. In this paper we focus on home automation using smart phone and computer. The iot devices controls and monitors the electronic electrical and the mechanical systems used in various types of buildings. The devices connected to the cloud server are controlled by a single admin which facilitate a number of users to which a number of sensor and control nodes are connected. The admin can access and control all the nodes connected to each user but a single user can control only the nodes to which the user itself is connected. This whole system using Internet of Things (iot) will allow mobile devices and computers to remotely control all the functions and features of home appliances from anywhere around the world using the internet connection. The system designed is economical and can be expanded as it allows connection and controlling of a number of different devices.

Home automation using Internet of Thing

Sign Language Recognition (SLR) system is a method which allow deaf people to communicate with society. In this study, Real-Time Sign Language recognition system was proposed by using the surface Electromyography (sEMG). To this purpose, sEMG data acquired from subject right forearm for all twenty six American Sign Language gestures. Raw sEMG data was filtered, feature extracted and fed into classification. Support Vector Machine (SVM) with one vs. all approach was used for multi class classification. The experiment result of offline system is reaching a recognition rate of 91.% accuracy and real-time system has a recognition rate of 82.3% accuracy. The results of the proposed system shows that sEMG signal can be used for Real-Time SLR systems.

Real-Time American Sign Language Recognition System Using Surface EMG Signal

Sign Language Recognition (SLR) system is a novel method that allows hard of hearing people to communicate with society. In this study, an American Sign Language (ASL) recognition system was proposed by using the surface Electromyography (sEMG). The objective of this study is to recognize the American Sign Language alphabet letters and allow users to spell words and sentences. For this purpose, sEMG signals are acquired from subject's right forearm for 27 American Sign Language gestures, 26 English alphabet letters, and one for home position. Time domain, frequency domain (band power), power spectral density (band power), and average power features were used as the feature extraction methods. After feature extraction, Principal Component Analysis (PCA) was applied to obtain uncorrelated features. As a classification method, Support Vector Machine and Ensemble Learning algorithm were used and their performances were compared with tabulated results. In conclusion, the results of this study show that sEMG signal can be used for SLR systems.

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American Sign Language Recognition system by using surface EMG signal

Technology stemming from web of things is home automation. World's main focus is to make a smart home to take advantage in providing comfort for human life. Web technology is a thing which is growing all the time. Embedded systems with Internet on Things (IoT) is becoming important and necessary part in the current IT industry and exhibiting potential market. Power consumption and efficiency with a user's comfort level is most important issue during this stage while performing various operations. Controller is suitable for power consumption in system and efficiency experiments with size factor. E-controller is represented by combining embedded technology with IoT. Real time information data monitoring of energy consumption is main objective of system. The paper introduces smart home system based on IoT with the help of Web application.

IoT based smart home with real time E-metering using E-controller

Sign language is a widely used and accepted standard for communication by people with hearing and speaking impairments. A sign language is a language which uses visually transmitted sign patterns, instead of acoustically conveyed sound patterns, to deliver the meaning. Several ways to generalize the American sign language recognition have been proposed in the past [14] [15]. In this paper, novel method of American sign language recognition with Shape and Texture features has been proposed. Many of the existing systems require the person gesticulating to use special data acquisition devices like data gloves which are expensive and difficult to handle. We proposes a more flexible vision based approach where the person is free from additional equipment. The Shape features and Texture feature are more unique, so a novel technique based on combination of these is derived and proposed here. For extracting shape features standard gradient operator such as Robert, Prewitt, Sobel, Canny, Freichein, Kirsh and Laplace are used and for texture feature vector quantization techniques are used. The gradient mask images of the character images are obtained and then LBG vector quantization algorithm is applied on these gradient images to get the codebooks of various sizes. These obtained LBG codebooks are considered as shape texture feature vectors for American sign language recognition. The database includes 26 for American sign language alphabets taken by 12 different people. The images are saved in a jpeg file format and stored in separate folder. Thus there are total 312 images were use for our project and 8 code book sizes (from 4 to 512). The nearest neighbour (KNN) algorithm is considered as performance comparison criteria for proposed character recognition techniques. The best performance is observed in LBG for codebook size 8 of Canny operator and the next best is seen for codebook sizes 4 of freichein gradient mask for feature extraction. The LBG VQ [11] design algorithm is an iterative algorithm which requires an initial codebook C. This initial codebook is obtained by the splitting method. In this method, an initial code vector is set as the average of the entire training sequence. This code vector is then split into two. The iterative algorithm is run with these two vectors as the initial codebook. The final two code vectors are splitted into four and the process is repeated until the desired number of code vectors is obtained.

Recognition of American sign language using LBG vector quantization

Information of the water wave properties is very important in a near shore region, in a ship, for level measurement in a tank, or for sea keeping and manoeuvring. In this work, we present a method based on X band radar using Linear Frequency Modulated Continuous Wave (FMCW) radar backscatter to estimate the various parameters of the wave like wave height, Doppler frequency, wave velocity, wave period, wind direction and possible way to detect breaking waves. Radar is developed at Society for Applied Microwave Electronic Engineering and Research (SAMEER) IIT BOMBAY campus. A wave tank has been used for experimentation in which probes generate water waves, The experiments are conducted at Hydraulics lab, Ocean Engineering department IIT Bombay.

Estimating Radar Backscatter from Water Wave Surface Using X Band FMCW Radar

Nowadays use of wireless technologies tremendously increased due to the continuous development of these technologies in various applications. One of the development in wireless technologies leads to deployment of the networks in which all mobile nodes will communicate via wireless links directly without use of any base station or predefined infrastructural support. These networks are self-organized networks called mobile ad hoc networks (MANETs) and architecture used for these networks will be either stand alone with one or few nodes communicating with base station or distributed. As communication is done through wireless links, these types of networks are more prone to several kinds of attacks. Authentication and encryption acts as first line of defense while an intrusion detection system (IDS) acts as a second line of defense. One of the intrusion detection system used in MANET is Enhanced Adaptive Acknowledgement (EAACK) which is based on acknowledgement packets for detection of malicious activities. This system increases the overhead of network significantly relative to other system such as watchdog. So, in this paper we adopt the hybrid cryptography to reduce the network overhead and enhance the security of networks significantly.

Hybrid cryptography mechanism for securing self-organized wireless networks

this paper presents the design and fabrication of a Planar Bi-Quad Antenna operating at 2. 45GHz. The modeling and simulation of the antenna is done using the CST Studio Suite (Student Edition) and the testing of the fabricated antenna is done using the Antenna Measurement System Kit (AMS Kit) developed by Akademica. This antenna shows improved bandwidth and characteristics over conventional wired Bi-quad antennas. Various antenna parameters such as Radiation Pattern, Directivity, VSWR, S11, etc. are calculated. A close agreement is found between the simulation and the experimental results.

Shital Mali

Papers

IoT based smart home with real time E-metering using E-controller

Recognition of American sign language using LBG vector quantization

Estimating Radar Backscatter from Water Wave Surface Using X Band FMCW Radar

Hybrid cryptography mechanism for securing self-organized wireless networks

Design and Performance Evaluation of a Planar Bi-Quad Antenna Operating at 2.4GHz