Advances of microprocessor design has been putting multiple cores on a single chip giving ways to internal parallel computing an exodus from increase in single clock frequency to provide remarkable growth in speed. What's significant is that each configuration presents itself to developer as a set of two or more cores capable of executing multiple tasks concurrently. Current advancements in industry highlight reconfigurable architectures as the new trend capable of conquering complexity of design, computational time and cost the primary research aspect of our paper. This research highlights the amendments/advancements in the chache memory for multi-core processor and its architecture for demonstrating its capability via reconfigurability. Due to abundant amount of data, many applications impose heavy resource requirements on the hardware platform. So our main purpose is to provide a simulation environment to applications demanding such heavy resource requirements.

Key words: Multi-core, Optimization, Reconfiguration, VHDL

[1]. Ibrahim A. Amory, " Design of two dimensional reconfigurable cache memory using FPGA." 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA).
[2]. A.D. Santana Gil and J.I. Benavides Benitez, "Reconfigurable Cache Implemented on an FPGA." 2010 International Conference on Reconfigurable Computing and FPGAs.
[3]. Po-Hao Hsu and Shao-Yi Chien, "Machine Reconfigurable cache memory architecture for integral image and integral histogram applications." 2011 IEEE Workshop on Signal Processing Systems (SiPS).
[4]. M X.-H. Sun, Y. Chen , "Reevaluating Amdahl's law multi-core era",‖ J. Parallel Distribution Computing. 70 (2010) 183-188
[5]. M. Hill, M. R. Marty, "Amdahl's law in the multicore era", IEEE Computer 41 (7)(2008) 33_38.

Huge amount of data is collected by the sensors from the end Subsequently, this considerably big amount of data must be processed, analyzed and stored in a cost effective ways. In this manner, an enormous pool of computing resources and storage must be provided to compute this vast amount of data. We focused on introducing the latest technologies such as sensors, IOT to radically revise approaches to agriculture by collecting the data about the various parameters of soil, analyze the data and performed the computations, giving the best optimal solutions for the farming. The application of computing in agricultural economy will open up a vast range of prospects, such as the vast storage of agriculture information, the cloud management of agricultural production process, the storage of agricultural economy information, early-warning and policymaking based on the agricultural products market, the tracing management of agricultural products quality

Key words: sensors; computing resources; IOT; ubidots.

[1]. Bhushan G. Jagyasi, Arun K. Pande, Ramesh Jain Event based Experiential Computing in "Agro-Advisory System for Rural Farmers", Wireless Communication©2017 IEEE.
[2]. Prathibha S R I, Anupama Hongal 2, Jyothi M P3 "IoT Based Monitoring System in Smart Agriculture", International Conference on Recent Advances in Electronics and Communication Technology, 2017.
[3]. Gokul L. Patil, Prasand S. Gawande and R. V. Bag "Smart Agriculture System based on IoT and its Social Impact", International Journal of Computer Applications (0975-8887), Vol. 176- No. 1, October 2017.
[4]. Tanmay Baranwal, Nitika , Pushpendra Kumar Pateriya "Development of IoT based Smart Security and Monitoring Devices for Agriculture", 6th International Conference - Cloud System and Big Data Engineering, 978-1-4673-8203-8/16, 2016 IEEE.
[5]. Narayut Putjaika, Sasimanee Phusae, Anupong Chen-Im, Dr. Phond Phunchongharn and Dr. Khajonpong Akkarajisakul "A Control.

In India about 6 million people are suffering from speech impairment and hearing impairment. People with speech impairment use sign languages to communicate with the society which is difficult for normal people to understand. Thus communication between deaf-mute people and normal people had always been a challenging task all over the world. Hence deaf mute communication required interpreter who will convert hand gestures into auditory speech. In past this project implementation involved the use of image processing concept and accelerometer. But the drawback of these implementations are projects were non portable and too expensive. Therefore system is being proposed with the use of flex sensors and accelerometer.

Keywords: Gesture Recognition, Sign Languages, Flex Sensors, Accelerometer.

[1]. Arthi M, Vijayalakshmi P, "Sign language to speech conversion," 5th International Conference on Recent Trends in Information Technology 2016.
[2]. Priyanka Lokhande, Riya Prajapati and Sandeep Pansare, "Data Gloves for Sign Language Recognition System" IJCA Proceedings on National Conference on Emerging Trends in Advanced Communication Technologies NCETACT, pp. 11-14, Jun 2015.
[3]. Vinod J Thomas, Diljo Thomas, "A Motion based Sign Language Recognition Method", International Journal of Engineering Technology, volume 3 Issue 4, ISSN 2349-4476, Apr 2015.
[4]. Sakshi Goyal, Ishita Sharma, Shanu Sharma,"Sign Language Recognition system for deaf and dumb people," International Journal of Engineering Research and Technology Vol.2 Issue 4, April 2013.
[5]. Ghotkar, Archana S., "Hand Gesture Recognition for Indian Sign Language", International Conference on Computer Communication and Informatics (ICCCI), 2012, pp 1-4.

People communicate with each other to convey their ideas, thoughts to the people around them. But this is impossible with deaf and mute people all over the world as they face struggle in expressing their feelings to other normal people. Sign language is the only solution to this problem which helps deaf-mute people to communicate. The aim behind this work is to develop a flex-sensor based gesture recognition module for recognizing the Sign Languages, which provides communication between people with speech impairment and normal people. The flex sensors and accelerometer are fitted over the data glove. The voltage signals will then processed by microcontroller and sent to voice module where the outputs are stored and produce appropriate voice with the help of speaker.

Key words: Gesture Recognition, Sign Languages, Flex Sensors, Accelerometer.

[1]. Sakshi Goyal, Ishita Sharma, Shanu SharmaSign, ―Language Recognition System For Deaf And Dumb People,‖ International Journal of Engineering Research & Technology (IJERT), April – 2013.
[2]. Abhijith Bhaskaran K, Anoop G Nair, Deepak Ram K, Krishnan Ananthanarayanan, H R Nandi Vardhan, ―Smart Gloves for Hand Gesture Recognition Sign Language to Speech Conversion System," International Conference on Robotics and Automation for Humanitarian Applications (RAHA), 2016.
[3]. Yun, L., ―A sign component based framework for sign language for Chinese sign Language Recognition Using Accelerometer and Semg Data,‖ IEEE Transaction on Biomedical Engineering, 2012.
[4]. Preetham c, ―Hand Talk Implementation of a Gesture Recognizing Glove,‖ India Educators' Conference (TIIEC), Texas Instruments, 2013.
[5]. Delliraj, M. and S. Vijayakumar., ― Design of Smart e- Tongue for the physically challenged people‖ International conference on Recent Trends in Information Technology (ICRTIT), 2013.

The primary objective of this work is to review the vehicle tracking system, discuss the challenges in Internet of Things (IoT) based vehicle tracking system. IoT is used to get intellectual connecting the objects with each other via information sensing in the physical world and broadcasting devices linked with the internet.This paper provides a comprehensive investigation on vehicle tracking system in association with the IoT and Big Data Analytics. This paper analyze the challenges pertaining to the IoT based Vehicle tracking system.This paper provides the novel methodology for assessing the quality of vehicle tracking system and identifies opportunity for future research in this area. Applications: The importance of QoE can be realized in vehicle tracking system for the improving the performance of the surveillance system.

Key words: GPS, IoT, IST, QoE, Vehicle Tracking System

[1]. Vehicle tracking Systems. Available from: https:// en.wikipedia.org/wiki/Vehicle_tracking_system
[2]. Building an intelligent transportation system with the Internet of Things (IoT), Available from: http:// www.intel.in/content/dam/www/program/embedded/ internet-of-things/blueprints /iot-building-intelligent-transport-systemblueprint. pdf
[3]. Lee SJ, Tewolde G, Kwon J. Design and implementation of vehicle tracking system using GPS/GSM/GPRS technology and smartphone application. IEEE World Forum on Internet of Things (WF-IoT); Seoul. 2014. p. 353–8.
[4]. He W, Yan G, Xu LD. Developing vehicular data cloudservices in the iot environment. IEEE Transactions on Industrial Informatics. 2014; 10(2):1587–95.
[5]. Mahendran D, Gopi M, Priyadharshini S, Karthick R. A study on cloud resource management techniques. International Journal of Innovative Research in Computer and Communication Engineering. 2013; 1(1):58–61.

Security in travel is primary concern for everyone.IOT based monitoring of vehicle parameters is described of effective information system that can monitor an automotive / vehicle / car condition in traveling. This project is designed to inform about the location of vehicle, vibration and temperature information that is occurred to a vehicle. This project uses accelerometer sensor which can detect the unevenness of vehicle and if vibrations occurred then a threshold limit. The signal send by the sensor are received by the microcontroller. Vehicle monitoring system uses wifi-module to send information over IOT. This monitoring system is composed of a GPS receiver, ARM-7, ACCELEROMETER, HEAT SENSOR and GPS Receiver who gets the geo satellite information in the form of latitude and longitude. The ARM -7 processes this information and this processed information is sent to the user/owner using WIFI-MODULE modem . A wifi modem is interfaced to the MCU. Heat sensor used to detect temperature level.

Key words: IOT, WiFi Module, ARM-7,Accelerometer, Heat sensor.

[1]. Mayuresh Desai ,Arati Phadke ,"Internet of Things based vehicle monitoring system", 2017 IEEE.
[2]. Rahul B. Pendor , P. P. Tasgaonkar," An IoT Framework for Intelligent vehicle monitoring System", International Conference on Communication and Signal Processing, April 6-8, 2016, India
[3]. Shulong Wang1, 2, Yibin Hou*1, 2, Fang Gao1, 2 and Xinrong Ji ,A Novel IoT Access Architecture for VehicleMonitoring System. 2016 IEEE
[4]. Kiran Sawant, Imran Bhole, Prashant Kokane, Piraji Doiphode, Prof. Yogesh Thorat, "Accident Alert and Vehicle Tracking System", International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 5, May 2016.
[5]. Mrs Manasi Patil, Aanchal Rawat, Prateek Singh, Srishtie Dixit, "Accident Detection and Ambulance Control using Intelligent Traffic Control System", International Journal of Engineering Trends and Technology (IJETT) ,Volume 34-Number 8,April 2016.

Human face plays an important role in our Social interaction, conveying people's identity but it is a dynamic object and has a high degree of variability in its appearances. So to overcome this variability Face Detection and face recognition methods have been introduced. Face detection is the basic step of face recognition. In this paper, we present a comprehensive and critical survey of face detection and face recognition techniques

Key words: Face detection, Face recognition.

[1]. M. Turk and A. Pentland, "Eigenfaces for recognition," Journal of Cognitive Neuroscience, vol. 3, no. 1, pp.71-86, 1991.
[2]. Sushma Jaiswal, Sarita Singh Bhadauria and Rakesh Singh Jadon 2011 comparison between face recognition algorithm Eigen faces fisher faces and elastic bunch graph matching Journal of Global Research in Computer Science
[3]. Kirby M and L. Sirovich 1990Application of the Karhunen-Loeve procedure for the characterization of human faces IEEE Transaction Patt. Anal. Mach. Intell.
[4]. Laurenz Wiskott, Jean-Marc Fellous, Norbert Krüger, and Christoph von der Malsburg 1997 Face Recognition by Elastic Bunch Graph Matching IEEE Transactions on pattern analysis and machine Intelligence published.
[5]. Face Detection and Recognition using Raspberry Pi Ishita Gupta1, Varsha Patil2, Chaitali Kadam 3, Shreya Dumbre4 Kennedy Road, Pune, India 2 Savitribai Phule Pune University

Attendance for the students is an important task in class. If we do manually it generally wastes a lot of productive time of the class. The solution for the current problem is through automation of attendance system using face recognition. Face is the primary identification for any human. This project describes the method of detecting and recognizing the face in real-time using Raspberry Pi. Project describes an efficient algorithm using open source image processing framework. Our approach has five modules – Face Detection, Face Pre-processing, Face Training, Face Recognition and Attendance Database. The software database is collected to recognize the faces of the students. The system will initially trained with the student`s faces which is collectively known as student collection database. The system uses easy interface to maximize the user experience

Key words: Raspberry Pi, Haar cascade, Edge Detection, Viola-Jones framework.

[1]. Viola, P., & Jones, M. (2001). Rapid object detection using a boosted cascade of simple features. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on (Vol. 1, pp. I-511). IEEE.
[2]. Rohit, C., Baburao, P., Vinayak, F., &Sankalp, S.(2015).Attendance management system using face recognition. International Journal for Innovative Research in Science and Technology, 1(11), 55-58.
[3]. NirmalyaKar, MrinalKanti Debbarma, AshimSaha, and DwijenRudra Pal, ―Implementation of Automated Attendance System using Face Recognition‖, International Journal of Computer and Communication Engineering, Vol. 1, No. 2, July 2012.
[4]. Benfano Soewito, Ford Lumban Gaol,‖ Attendance System on Android Smartphone‖, 2015 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC).

Waste management is a big issue in the world. Many countries provide different methods for garbage management and maintain cleanliness of surroundings. In India there is improper waste management and people also not maintain the cleanliness of environment. At many places the garbage containers are overflow but GCT (Garbage Collection Truck) not arrives. Also with the increase in the population of country current garbage collection system not capable to maintain the green environment.. Here we actually use arduino board connected to an ultrasonic sensor and a Wi-Fi module and this entire system is connected to every single bin inside the campus area. As the Internet of things (IoT) is giving us unique solutions to everyday problems, we propose a smart garbage alert system for efficient waste monitoring.

Key words: Smart Devices; Internet of Things, Android ; Garbage Monitoring System.

[1]. Fetulhakabdurahman, Sileshiaweke ,Cheraassefa "Automated Garbage Monitoring System Using Arduino" iosr Journal of Computer Engineering (IOSR-JCE) , Volume 20, Issue 1, Ver. I (Jan.- Feb. 2018), PP 64-76.
[2]. Swarna m1, k j anoop2, k kanchana "Iot Based Garbage Box Monitoring System" International Journal of Pure and Applied Mathematics Volume 119 No. 15 2018, 2713-2723.
[3]. Dr. K. Alice Mary, Perreddy Monica, A. Apsurrunisa, Chathala Sreekanth "IOT Based Garbage Monitoring System" International Journal of Scientific & Engineering Research, Volume 8, Issue 4, April-2017
[4]. Ashima Bajaj and ,Sumanth Reddy "Garbage Monitoring System Using IOT" International Journal of Pure and Applied Mathematics Volume 114 No. 12 2017, 155-161
[5]. Parkash, Prabu, "IOT Based Waste Management for Smart City", International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 2, February 2016.

Waste management is one of the primary problems faced in India irrespective of the case of developed or developing regions. The key issue in the waste management is that the garbage bins at public places gets overflowed well in advance before the commencement of the next cleaning process. It in turn leads to various hazards such as bad odor and ugliness to that place which may be the root cause for the spread of various diseases. Healthy environment is imperative to a healthy and a happy community so this problem needs to be tackled smartly. As the Internet of things (IoT) is giving us unique solutions to everyday problems, we propose a smart garbage alert system for efficient waste monitoring. The proposed system will consist of waste bins that are equipped with ultrasonic sensors ,DHT 11, Gas sensor which are interfaced with Arduino Uno and a Wi-Fi module...

Key words: Smart Devices; Internet of Things , Android , Garbage Monitoring System.

[1]. Fetulhakabdurahman, Sileshiaweke ,Cheraassefa "Automated Garbage Monitoring System Using Arduino" iosr Journal of Computer Engineering (IOSR-JCE) , Volume 20, Issue 1, Ver. I (Jan.- Feb. 2018), PP 64-76.
[2]. Swarna m1, k j anoop2, k kanchana "Iot Based Garbage Box Monitoring System" International Journal of Pure and Applied Mathematics Volume 119 No. 15 2018, 2713-2723.
[3]. Dr. K. Alice Mary, Perreddy Monica, A. Apsurrunisa, Chathala Sreekanth "IOT Based Garbage Monitoring System" International Journal of Scientific & Engineering Research, Volume 8, Issue 4, April-2017
[4]. Ashima Bajaj and ,Sumanth Reddy "Garbage Monitoring System Using IOT" International Journal of Pure and Applied Mathematics Volume 114 No. 12 2017, 155-161
[5]. Parkash, Prabu, "IOT Based Waste Management for Smart City", International Journal of Innovative Research in Computer and Communication Engineering, Vol. 4, Issue 2, February 2016.

The underground sewerage Pipeline systems are responsible for transporting vital materials . Any leakage in the pipe can cause major financial losses and possible environmental damages. Currently, buried pipelines are only monitored at key points, which can be spaced several kilometers apart. A system with a higher spatial resolution would provide operators with a better understanding of their network. In buried pipeline monitoring, sensor nodes are deployed in soil. The underground environment imposes major limitations on sensor nodes, as poor RF transmission and lack of maintainability. The prior alerts of blockages and locate them using IOT. Trace location using GPS and send SMS through GSM. This review paper covers contribution from various researches in this area.

Key words: RF, GPS, SMS, GSM, IOT .

[1]. Ms T.Deepiga ,"Smart Water Monitoring System Using Wireless Sensor Network at Home"International Research Journal of Engineering and Technology –IEEE 2395-0056 Volume: 02 Issue: 04 | July-2015.
[2]. Zulhani Rasin, " Water Quality Monitoring System Using Zigbee Based Wireless Sensor Network'' International Journal of Engineering & Technology IEEE Vol:09 No:10.
[3]. Hua-Ping YU, "Deployment Algorithms of Wireless Sensor Networks for Near-surface Underground Oil and Gas Pipeline Monitoring'' Sensors & Transducers, Vol. 174, Issue 7, July 2014, pp. 95-102.
[4]. Deepthi.V, Karthika.K, Kowsika.R*, Siva Keerthana and R. Sudarmani, " Study of Gully Pot Monitoring System for Urban Areas" International Journal of Current Engineering and Technology ©2018 INPRESSCO®, Received 16 Dec 2017, Accepted 17 Feb 2018, Available online 22 Feb 2018, Vol.8, No.1 (Jan/Feb 2018).
[5]. Daniel Granlund, Robert Brännström "Smart City: The Smart Sewerage" IEEE Workshop On User MObility and VEhicular Networks 2017. Volume6656/2011, 447-462.

The underground sewerage Pipeline systems are responsible for transporting vital materials . Any leakage in the pipe can cause major financial losses and possible environmental damages. Currently, buried pipelines are only monitored at key points, which can be spaced several kilometers apart. A system with a higher spatial resolution would provide operators with a better understanding of their network. In buried pipeline monitoring, sensor nodes are deployed in soil. The underground environment imposes major limitations on sensor nodes, as poor RF transmission and lack of maintainability. The prior alerts of blockages and locate them using IOT. Trace location using GPS and send SMS through GSM.

Key words: RF, GPS, SMS, GSM, IOT

[1]. Ms T.Deepiga ,"Smart Water Monitoring System Using Wireless Sensor Network at Home"International Research Journal of Engineering and Technology –IEEE 2395-0056 Volume: 02 Issue: 04 | July-2015.
[2]. Zulhani Rasin, " Water Quality Monitoring System Using Zigbee Based Wireless Sensor Network'' International Journal of Engineering & Technology IEEE Vol:09 No:10.
[3]. Hua-Ping YU, "Deployment Algorithms of Wireless Sensor Networks for Near-surface Underground Oil and Gas Pipeline Monitoring'' Sensors & Transducers, Vol. 174, Issue 7, July 2014, pp. 95-102.
[4]. Deepthi.V, Karthika.K, Kowsika.R*, Siva Keerthana and R. Sudarmani, " Study of Gully Pot Monitoring System for Urban Areas"

The pre-processing is a series of operations performed on scanned input image. It essentially enhances the image rendering it suitable for segmentation. The role of pre-processing is to segment the interesting pattern from the background. Generally, noise filtering, smoothing and normalization should be done in this step. The pre-processing also defines a compact representation of the pattern. Binarization process converts a gray scale image into a binary image. Dilation of edges in the binarized image is done using sable technique. this system will be suitable for converting character documents into structural text form and recognizing character names.

Key words: Handwritten character recognition, Image processing , Feature extraction, feed forward.

[1]. Wong Yoong Xiang, Patrick Sebastian, "Handwriting Recognition Using Webcam for Data Entry " 2015 IEEE 11th International Colloquium on Signal Processing & its Applications (CSPA2015), 6 -8 Mac. 2015
[2]. W. L. Gogh, D. P. Mittal, and H. A. Bari, "An artificial neural network approach to handwriting recognition," in Knowledge Based Intelligent Electronic Systems, 1997. KES '97. Proceedings.1997 First International Conference on, 1997, pp. 132-136 vol.1..
[3]. K. Pyeoung Kee, "Improving handwritten numeral recognition using fuzzy logic," in TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE, 1997, pp. 539-542 vol.2.".
[4]. M. Y. Chen, A. Kundu, and J. Zhou, "Off-line handwritten word recognition (HWR) using a single contextual hidden Markov model," in Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on, 1992, pp. 669-672.
[5]. Wan, Y. Huang, G. Zhang, and C. Wan, "Offline Handwritten Numeral Recognition Based on Principal Component Analysis," in Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on, 2007, pp. 1-298-1-302

An handwritten alphabetical character recognition system using multilayer feed forward neural network is described in the paper. A new process, known as, feature extraction the features of the handwritten alphabets. 50 data sets, each containing twenty six alphabets written by various people, are used for training the neural network and 570 different handwritten alphabetical characters are used for testing. This recognition system gives quite well extraction higher levels of recognition accuracy which has effective systems employing the conventional of feature extraction. This system helps for converting handwritten documents into normal text form and recognizing handwritten alphabets.

Key words: Handwritten character recognition, Image processing , Feature extraction, feed forward.

[1]. Wong Yoong Xiang, Patrick Sebastian, ―Handwriting Recognition Using Webcam for Data Entry ‖ 2015 IEEE 11th International Colloquium on Signal Processing & its Applications (CSPA2015), 6 -8 Mac. 2015
[2]. W. L. Goh, D. P. Mital, and H. A. Babri, "An artificial neuranetwork approach to handwriting recognition," in KnowledgeBased Intelligent Electronic Systems, 1997. KES '97. Proceedings.1997 First International Conference on, 1997, pp. 132-136 vol.1
[3]. K. Pyeoung Kee, "Improving handwritten numeral recognition using fuzzy logic," in TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications., Proceedings of IEEE, 1997, pp. 539-542 vol.2.‖.
[4]. M. Y. Chen, A. Kundu, and J. Zhou, "Off-line handwritten word recognition (HWR) using a single contextual hidden Markov model," in Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on, 1992, pp. 669-672.
[5]. . Wan, Y. Huang, G. Zhang, and C. Wan, "Offline Handwritten Numeral Recognition Based on Principal Component Analysis," in
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on, 2007, pp. 1-298-1-302

Epilepsy patients encounter difficulties in day by day life because of safety measures they need to take so as to adapt to this condition. At the point when a seizure happens, it may cause wounds or imperil the life of the patients or others, particularly when they are utilizing substantial hardware, e.g., determining autos. Investigations of epilepsy regularly depend on electroencephalogram (EEG) motions so as to break down the conduct of the cerebrum amid seizures. Finding the seizure time frame in EEG accounts physically is troublesome and tedious; one frequently needs to skim through tens or even several hours of EEG chronicles. Hence, programmed identification of such an action is of extraordinary significance. Another potential utilization of EEG flag examination is in the expectation of epileptic exercises previously they happen, as this will empower the patients (and parental figures) to avoid potential risk. In this paper, we first present a diagram of seizure identification and forecast issue and give bits of knowledge on the difficulties around there.

Key words: Gesture Component Analysis Dual Tree Discrete Wavelet, Seizure Detection, EEG, FPGA

[1]. "VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability" Lichen Feng, Zunchao Li, andYuanfa Wang(2017).
[2]. "Clustering Challenges on Biological Networks" S. Butenko, W. A. Chaovalitwongse and P. M. Pardalos, World Scientific (2009).
[3]. "Feature Selection for Consistent Biclustering via Fractional 0-1 Programming" (with Stanislav Busygin and Oleg A. Prokopyev), Journal of Combinatorial Optimization, Volume 10, Number 1 (2005), pp. 7-21.
[4]. "Biclustering in Data Mining" (with S. Busygin, and O. Prokopyev), Computers & Operations Research, Volume 35, Issue 9 (2008), pp. 2964-2987.
[5]. "On Biclustering with Features Selection for Microarray Data Set" (with S. Busygin and O. Prokopyev), In (BIOMAT 2005) Proceedings of the International Symposium on Mathematical and Computational Biology (Edited by R. Mondaini & R. Dilao), World Scientific (2006), pp. 367-377.

Internet of Things has given us a new epoch of computing technology. Thoughts of creation that correlates a different means of considering the events with invented concepts that avail the possibilities proposed by new approaches in intelligent ways.In, The current scenario, asan air pollution is increasing, because of this pollution, we are going in open vehicle or in close vehicle such decision are taken.Most of the time, I identify, in red signal, People are not follow signals and vehicle not stop. And occur accident .so, for decreasing accident such point of view, project is decidedsome people are aware, some are not the engine on in red signal the fuel is waste in large amount when people are in red signal. But some people save fuel hence
environment cost is decreasingToday........

Key words: IOT, Smart city, LM35,8051microcontroller,PIC , Pollution Sensor, Ultrasonic sensor, Zigbee.

[1]. NehaFirdaushRaun "Smart environment using internet of things (IOTS) - a review" Published in 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
[2]. Madhvi A. Pradhan; SupriyaPatankar; AkshayShinde; VirendraShivarkar; PrashantPhadatare"IoT for smart city: Improvising smart environment" 2017 .
[3]. C. TejaswiniRoy ; D. Sri Lakshmi ; G. Anirudh Kumar ; H. N. Vishwas "International Conference On Smart Technologies For Smart Nation " 2017
[4]. AmanyAlnahdi; Shih-Hsi Liu "Mobile Internet of Things (MIoT) and Its Applications for Smart Environments" ,2017 IEEE International Congress on Internet of Things (ICIOT).
[5]. NeeharikaCherukutota ;ShraddhaJadhav "Architectural framework of smart water meter reading system in IoT environment",2016 International Conference on Communication and Signal Processing.412.

Nowadays internet of thing has changed people way of using technology. Devices operating using internet has evolved over the last few years. Due to the advancement of sensor technology the way of working has improved a lot that is speed, performance. In this project Iam developing a system smart city that is equipped with Internet of Things. In this System four modules are used such as, environmental parameter, accident detection, road signage, school/hospital. This system will help to improve the smart environment conditions and provide a better way of living. Thus our system will make the city better than the existing smart cities that are available.

Key words: IOT, Smart city, LM35, 8051microcontroller, PIC , Pollution Sensor, Ultrasonic sensor, Zigbee.

[1]. NehaFirdaushRaun "Smart environment using internet of things (IOTS) - a review" Published in 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
[2]. Madhvi A. Pradhan; SupriyaPatankar; AkshayShinde; VirendraShivarkar; PrashantPhadatare"IoT for smart city: Improvising smart environment" 2017 .
[3]. C. TejaswiniRoy ; D. Sri Lakshmi ; G. Anirudh Kumar ; H. N. Vishwas "International Conference On Smart Technologies For Smart Nation " 2017
[4]. AmanyAlnahdi; Shih-Hsi Liu "Mobile Internet of Things (MIoT) and Its Applications for Smart Environments" ,2017 IEEE International Congress on Internet of Things (ICIOT).
[5]. NeeharikaCherukutota ;ShraddhaJadhav "Architectural framework of smart water meter reading system in IoT environment",2016 International Conference on Communication and Signal Processing