Smart university by IJRTER

SMART UNIVERSITY Gangutai Uramanatti1, Rashmi Rachh2 1

Department of CSE, PG Center VTU Belagavi 2 Department of CSE,VTU Belagavi

Abstractâ&#x20AC;&#x201D; Universities spread education and employ lot of infrastructures. These infrastructures are managed by human effort in most cases and not cost or energy efficient. With emergence of sensor technologies, it is now possible to automate most of functionalities in the universities. But the command to operate the automation is located in a particular place in universities. With IOT gaining popular, if the automation system of university is integrated with IOT, it become easier to manage the entire operation of university. In this work, designed an IOT based smart university system to manage the operations of universities like automatic attendance. Power saving using PIR and Humidity sensors using Arduino microcontroller. Keywords:-Internet of Things; Arduino; Automation; PIR sensor; Humidity sensor I. INTRODUCTION Internet of Things (IoT) is a technology in which information is collected from sensors and connected devices that are uniquely identifiable and produce massive amount of data. IoT allocate things to sense and manage it across existing group, creating direct integration of the substantial world into computer based systems, and ensuing in better efficiency, exactness and economic benefit. [1][2] When IoT is improved with sensors and actuators, the machinery becomes an object of the more general class of systems, which also include technologies such as smart grids, smart homes, clever transportation and smart cities.[3][4] Rest of the paper explains by section wise. Section II gives about concept of system, III gives system architecture and results are explained in section IV and conclusion in V section. II. SMART UNIVERSITY CONCEPT University campuses are quite big and many infrastructure facilities like lighting, cooling, attendance etc are to be automated to efficiently manage the entire operations of university. Previously many automations like access control , RFID based attendance etc are proposed and each are individual systems which has to be maintained and managed separately, but this work is not a replacement for it , but a complete system to which others can be integrated and make their services.[1][2] The main objective of this automation is to reduce the energy wastage cost and improve the service delivery without any failures. Also the proposed system is supposed to work for 24 hours on all days and its control interface are available. So that administrator can suit the system according to needs. A. Application in smart university Smart university equipped with sensors and IOT can accomplish following 1. 2. 3. 4.

Monitoring the flow of people with possibility of opening and closing pathway. Lighting corridors and halls Automate attendance Reducing the electricity consumption

International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

B. Type of sensors that can be used in a smart university Passive Infra Red (PIR): sensors are used for many necessary projects or goods that require detecting when a person has exit or entered the area or approached.

Digital Humidity Temperature Sensor

This is the multifunctional sensor which provides warmth (temperature) and wetness (humidity) information at the equal time. It gives a trustworthy reading when state of atmosphere humidity lies in between twenty and ninety, and temperature condition in between zero and fifty degree centigrade, there is a need of cover up for mainly house and every day applications that do not hold tremendous condition. Modules include ď&#x201A;ˇ Smart Lighting: the system controls the operation of lights in entire university at all the spots ď&#x201A;ˇ Smart cooling: the system automatically adjusts fans for the temperature set by administrators. ď&#x201A;ˇ Smart attendance: the system does the attendance for students and staffs automatically. All the smart operations defined can be controlled and monitored in Control panel using IOT interface. III. SYTEM ARCHITECTURE The architecture of the system is given below PIR sensors are used to detect movement and placed in different places and wired to Aurdino microcontroller. [5-8] Temperature sensor is used to monitor the current temperature in class rooms, staff rooms and halls. [6-9] Device controller controls the current to fans and air coolers. Announcement Speaker is placed in different places in university through which announcements can be given. Cameras are placed in front of class room and staff room, labs etc and are wired to Aurdino microcontroller. [7]

International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

The system works as follows Administrator login to the control terminal and set the desired temperature criteria for cooling and this data moves to Aurdino microcontroller. Microcontroller watches the current temperature and when matches the rules set by microcontroller, device controller is used to control the fans and air coolers. Microcontroller continuously monitors the PIR sensors and when an intrusion detected, signal is sent to device controller to control the lights to switch on and automatic switch off if no persons detected or after a predefined duration. By this way lights are switched on only when any one needs it and thus energy is conserved. [11] Microcontroller catches images via web camera and passes to the Attendance system. Attendance system detects faces in images and matches to already trained faces in the database and once match is detected attendance is marked and no mark for not matching. Curve let transform and k-Nearest neighbor algorithms are used for catching and comparing images [12-15]. Discrete Curve let algorithm Step1: Read the information picture. Step 2: Use 2 scales and sixteen directions to select levels and scales of curve let transform. Step 3: Using wrapping function apply fast discrete curve let transform to input image Step 4: Use the resulting sub band, to extract the edge after applying edge detector. Step 5: To map the edges onto the original image use inverse curve let transform. K-Nearest Neighbour (KNN) algorithm This is the one of the instance based method. It imagines all instances keep up a correspondence to points in the n-dimensional space Rn. The closest neighbors of an instance are defined in terms of the standard Euclidean distance. Nearest neighbour: ď&#x201A;ˇ Allocate nearest training example xn, then estimate f (xq)=f(xn) by given query instance xq. [4.1] K-Nearest neighbour: ď&#x201A;ˇ Given xq, assign weight to all k nearest neighbors(if discrete-valued target function) ď&#x201A;ˇ Take mean of f values of k nearest neighbors (if real-valued)

International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

f (xq) = 1/k

(xi)

[4.2]

Instances that taken in the k-Nearest Neighbour algorithm are points in two-dimensional space and the target function are a Boolean value. xq is a query point which is matched with the training examples. Using control terminal, we can view the attendance data. Also we can see the energy consumption in university aggregated over a period of time. IV. RESULTS In this work we implemented the system and tested it as proof of concept and found it is working accurately. From the control terminal temperature condition for cooling of rooms can be controlled by using humidity sensor. The energy consumption over a period of time through control terminal can be viewed.Attendance system can be trained with different faces of students.It detects face and shows the attendance report on the control terminal. Announcement is played based on the conditions set. V. CONCLUSION In this work, we have implemented a smart university system for better energy management. We have added IOT interface system to it and made remote management possible, In addition we have applied automatic face detection, tracking and implemented a smart attendance system for staff and students. In future this can be extended by including the following applications.  Traffic flow by locating and indicating the direction of the location on the university.  Prevention of accidents and disasters through constant monitoring of noise, smoke and halls of institutions.  Smart Parking: avoiding jams and accidents by monitoring and finding vacancies of places for parking of vehicles for students and staff members. REFERENCES 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

13. 14. 15.

Steffen Sorrell, “The Things in the Internet of Things: Consumer, Industrial & Public Services 2015-2020,” Eds. Juniper, 2015. Somayya Madakam, “Internet of Things: Smart Things,” International Journal of Future Computer and Communication, vol. 4, no. 4, Aug 2015. Li Yu vangLu and XiaoJuan Zhu, “Smart Hospital based on Internet of Things,” Journal of Networks, vol. 7, no. 10, Oct. 2012. E. Wasserman, “Riding herd: RFID tracks live-stock,” 2009 https://www.arduino.cc/en/Guide/Introduction https://learn.adafruit.com/PIR passive infrared I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey on sensor networks,” IEEE Commun. Mag., vol. 40, no. 8, pp. 104–112, Aug. 2002. J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Comput. Netw., vol. 52, no. 12, pp. 2292– 2330, Aug. 2008. M. Winkler, K.-D. Tuchs, K. Hughes, and G. Barclay, “Theoretical and practical aspects of military wireless sensor networks,” J. Telecommun. Inf. Technol., vol. 2, pp. 37–45, Apr. /Jun. 2008. http://www.teenengineeringprojects//dht11-humidity-temparature-sensor Kadam Shah, Prakash Savaliya and Mitesh Patel, “Automated room light controller with bidirectional visitor counter,” IJICTRD-International Journal of ICT Research and Development, vol. 1, issue 4, Naveed Khan Balcoh, M. Haroon Yousaf, Waqar Ahmad and M. Iram Baig, “Algorithm for Efficient attendance Management: Face recognition based approach,” IJCSI International Journal of Computer Science Issues, vol. 9, issue 4, no. 1, Jul. 2012 http://www.codeproject.com//Articles/175557/Plot-path Mrunmayee Shirodkar, “Automated Attendance Management System using Face Recognition,” International conference and workshop on Emerging trends in Technology (ICWET), Mumbai, India 2015 http://class.coursera.org/machlearning-001/ lecture/203