Home automation-controlling the fans, lights and other electrical appliances in a house using Internet of things is widely preferred in recent days. In this paper, we propose a web application using which the fans, lights and other electrical appliances can be controlled over the Internet. The important features of the web application is that firstly, we have a chatbot algorithm such that the user can text information to control the functioning of the electrical appliances at home. The messages sent using the chatbot is processed using Natural Language processing techniques. Secondly, any device connected to the local area network of the house can control the devices and other appliances in the house. Thirdly, the web application used to enable home automation also has a security feature that only enables certain users to access the application. And finally, it also has a functionality of sending an email alert when intruder is detected using motion sensors. © 2017 IEEE.

Swathi Jamjala Narayanan

Department of Software Systems

School of Computer Science and Engineering

Vellore Campus

C. J. Baby

F. A. Khan

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

2017 Innovations in Power and Advanced Computing Technologies (i-PACT)

The main purpose of the paper is to construct a prototype of a spoon which senses the hand motion of an individual suffering from Parkinson's disease. It gives a counter motion to the trembling actions of a patient's hand, in order that they don't spill their food. The movement of the hand acts like feedback to a microcontroller that operates two servos that provide counter-motion. There are Inertial Measurement Units positioned on the spoon that measure the deviations in yaw, pitch, and roll of the spoon and thus govern the counter balancing action of the servos. A PID controller is used to maintain a tilt to the spoon's angle and as a consequence the spoon is kept at a level plane. Features such as IoT and Machine Learning have been integrated into the system, that enables the product to monitor changes. IoT is used in the device to monitor the sensor reading remotely and analyze the progress of the patient. Machine Learning is used to detect any anomalies in the sensor data from the device. If an anomaly is detected the device send a mail alert to the well-wishers of the patient.

2018 International Conference on Communication and Signal Processing (ICCSP)

Parkinson's Disease Assist Device Using Machine Learning and Internet of Things

Detecting users in an indoor environment based on Wi-Fi signal strength has a wide domain of applications. This can be used for objectives like locating users in smart home systems, locating criminals in bounded regions, obtaining the count of users on an access point etc. The paper develops an optimized model that could be deployed in monitoring and tracking devices used for locating users based on the Wi-Fi signal strength they receive in their personal devices. Here, we procure data of signal strengths from various routers, map them to the user’s location and consider this mapping as a classification problem. We train a neural network using the weights obtained by the proposed fuzzy hybrid of Particle Swarm Optimization &amp; Gravitational Search Algorithm (FPSOGSA), an optimization strategy that results in better accuracy of the model. © Springer Nature Singapore Pte Ltd. 2017.

Advances in Intelligent Systems and Computing Proceedings of Sixth International Conference on Soft Computing for Problem Solving

User Localization in an Indoor Environment Using Fuzzy Hybrid of Particle Swarm Optimization &amp; Gravitational Search Algorithm with Neural Networks

Due to prevalent availability of wireless networks, there is enormous usage of mobile devices among the public in all sectors. Locating the mobile devices using the wireless signal strength received enables transparent and immediate services for both indoor and outdoor users. For indoor users, a smart environment could be provided by giving smart facilities like automating switching on/off of room lights, air conditioning, etc., by finding the user's exact location using their mobile device. Similarly, outdoor users can get services from the mobile service providers based on their current location. In this paper, we consider indoor user localisation as a pattern classification problem and propose to apply fuzzy decision tree (FDT) for locating users. As far as our knowledge is concerned, this is the first attempt to apply FDT for locating users in indoor environment using wireless signal strength received by user's handheld devices. Copyright © 2016 Inderscience Enterprises Ltd.

Journal	Data powered by Typeset2017 Innovations in Power and Advanced Computing Technologies (i-PACT)
Publisher	Data powered by TypesetIEEE
Open Access	No