_______________________________________________________________________________________________
_______________________________________________________________________________________________
Automation for Smart Homes with WSN and GPRS Technology
1P D S SSSiva Durga, 2P.BalaMurali Krishna
1,2Dept of ECE, Sri Mittapalli Institute of Technology for Women, Tummalapalem, A.P, India
Abstract: Smart home environments have achieved a high prior to the point where everyday objects and devices at home can be networked to give the inhabitants new means to control them. Advances in digital electronics have enabled the development of size (small) and communication (in short distances through sensor nodes).
They are low-cost, low-power and multifunctional. The sensor nodes consist of sensing components, data processing, and communication components, leverage the idea of Wireless Sensor Networks (WSN) based on collaborative effort of a large number of nodes. There are a large number of researches dealing with WSN applications, but still it is possible to explore in WSN development and maintenance. This Research examines the possibility of integration WSN and the service robots into a smart home application. The service robots can be considered to be mobile nodes that provide additional sensorial information, improve/repair the connectivity and collect the information from wireless sensor nodes. On the other hand, the WSN can be considered as an extension of the sensorial capabilities of the robots and it can provide a smart environment for the service robots.
Index Terms- Microcontroller, Sensors, GPRS, Robot, Camera, Devices, ZIGBEE.
I. INTRODUCTION
A smart environment is a physical world that involves an interconnection through a continuous network abundantly and invisibly with sensors, actuators and computational units, embedded seamlessly in the everyday objects of our lives .A smart home is a residence in which computing and information technology is applied to respond on the immediate basis to the occupant's needs. It can be used to enhance and develop the everyday life at home. The potential applications for smart homes can be found in these priority categories: communication, entertainment, welfare, environment, safety, and appliances .Wireless Sensor Networks (WSNs) have become an attractive technology for the research community, particularly with the proliferation in Micro-Electro Mechanical Systems (MEMS) technology which has facilitated the development of smart sensors. Typically, a WSN is a distributed system that is composed of autonomous units with sensing capabilities (sensor nodes), interconnected by wireless communication system. This network offers potentially low-cost solution to several problems including military target tracking, health care monitoring, environment control systems, animal
monitoring, and Smart Homes .The WSN is built of sensor nodes, from a few to several thousands in number where each node is connected to one or several sensors.
II. EXISTINGSYSTEM HARDWARE DESIGN FOR SMART HOME NETWORK
In this work, we assume that no matter where the user is, the coordinator will always be connected to the monitoring center/server via a computer that can access the Internet or the GPRS network [1]. It can obtain all messages exchanged between the server and the network. When the server sends out a command, the CPU of the network coordinator will read the content of the command and get the details by analyzing it, such as turning on the air conditioner or refrigeration. The main control program within the network coordinator writes the details to the ZIGBEE module through serial ports.
Then the ZIGBEEmodule will be responsible for sending the messages to the family network. From Fig. 1 we can see that development of the network coordinator and the ZIGBEEnode is the most important task for hardware system design. These two components are basically identical. The only difference is that the latter has the function of GPRS communications while the former does not. Therefore, we will focus on describing the design of the ZIGBEE network coordinator in this paper. According to the above description, we can find that the microcontroller (MCU), the ZIGBEE module, and the GPRS module are the most important parts of the network coordinator. The hardware construction of our coordinator node adopts MSP430F149 as MCU (from TI), ETRX2 ZIGBEE module, and MC52i GPRS module (from Siemens).
III. PROPOSEDSYSTEM HARDWARE DESIGN FOR SMART HOMENETWORK
In this work we use WSN to create a smart environment.
The wireless sensor Nodes [2] can be embedded into the smart devices, and they can communicate each other by wireless. By placing slave sensor nodes everywhere in the house, the temperature, illumination, fire, gas leakage, water leakage, intruders detect information can be passed to a PC collecting the information from the master node. Whenever, the critical condition arises, a buzzer will alert the user to take required action through the PC.
The service robot in the smart home environment has the following key functionalities [3]: navigation, object picking and object Handling. To execute the functions, a classical robotic platform should be equipped with sensors such as Temperature sensor, an ultrasonic sensor, a LDR sensor, humidity sensor or a camera as well is fitted on its top.The proposed system consists of two sections and they are mentioned as below:
3.1ROOM SECTION
This section describes about room section. The below figure 1 shows the block diagram of the room section.
Room section contains LPC2148 microcontroller, ZIGBEE module, different sensors, LCD display and power supply circuit. The design of this proposed system is explained as follows.The below fig.2 shows smart home network for controlling the actions.
Fig.1: Block diagram of room section
Fig.2: Smart home network.
3.1.1 LPC2148 Micro controller
LPC2148 is the widely used IC from ARM-7 family. It is manufactured by Philips (NXP) and it is pre-loaded with many inbuilt peripherals making it more efficient and a reliable option for the beginners as well as high end application developer. In this paper, LPC2148 is used, which is a 16 bit micro controller. It consists of three inbuilt timer/counter which will be used for the
timer configuration.The below Fig.3.Shows LPC2148 microcontroller.
Fig.3:LPC2148 microcontroller 3.1.2 ZIGBEE
ZIGBEE modules feature a UART interface, which allows any microcontroller or microprocessor to immediately use the services of the ZIGBEE protocol [4]. All a ZIGBEE hardware designer has to do in this case is ensure that the host’s serial port logic levels are compatible with the XBee’s 2.8- to 3.4-V logic levels.
The logic level conversion can be performed using either a standard RS-232 IC or logic level translators such as the 74LVTH125 when the host is directly connected to the XBee UART. Data is presented to the X-Bee module through its DIN pin, and it must be in the asynchronous serial format, which consists of a start bit, 8 data bits, and a stop bit. Because the input data goes directly into the input of a UART within the X-Bee module, no bit inversions are necessary within the asynchronous serial data stream. All of the required timing and parity checking is automatically taken care of by the X-Bee’s UART.
ZIGBEE supports protocols for defining a type of sensor network that controls applications used in residential and commercial settings such as air conditioning, heating and lighting. It harmonizes the application software layers specified by the ZIGBEE alliance and the IEEE 802.15.The below Fig.4.ShowsZIGBEE module.
Fig.4:ZIGBEE Module 3.1.3 CO SENSOR
They are used in gas leakage detecting equipment in home and industry, are suitable for detecting of LPG, i- butane, propane, methane, alcohol, Hydrogen, smoke.The below fig.5 shows Co-sensor.
_______________________________________________________________________________________________
Fig.5: Co Sensor 3.1.4 Temperature sensor:
The LM35 is an integrated circuit sensor that can be used to measure temperature with an electrical output proportional to the temperature (in oC) .The LM35 - An Integrated Circuit Temperature Sensor .You can measure temperature more accurately than a using a thermistor. The sensor circuitry is sealed and not subject to oxidation, etc. The LM35 generates a higher output voltage than thermocouples and may not require that the output voltage be amplified. The below fig.6 shows temperature sensor.
Fig.6: Temperature Sensor 3.1.5 HUMIDITY:
Humidity is the amount of water vapor in the air. In daily language the term "humidity" is normally taken to mean relative humidity. Relative humidity is defined as the ratio of the partial pressure of water vapor in a parcel of air to the saturated vapor pressure of water vapor at a prescribed temperature. Humidity may also be expressed as absolute humidity and specific humidity. Relative humidity is an important metric used in forecasting weather. Humidity indicates the likelihood of precipitation, dew, or fog. High humidity makes people feel hotter outside in the summer because it reduces the effectiveness of sweating to cool the body by preventing the evaporation of perspiration from the skin. Absolute humidity is the quantity of water in a particular volume of air. The most common units are grams per cubic meter, although any mass unit and any volume unit could be used.The below fig -7 shows humidity sensor.
Fig.7: Humidity Sensor 3.1.6 LIGHT DEPENDENT RESISTORS:
LDRs or Light Dependent Resistors are very useful especially in light/dark sensor circuits. Normally the resistance of an LDR is very high, sometimes as high as
1000 000 ohms, but when they are illuminated with light resistance drops dramatically.The below fig.8 shows LDR.
Fig.8: LDR
The general purpose photoconductive cell is also known as LDR – light dependent resistor. It is a type of semiconductor and its conductivity changes with proportional change in the intensity of light. The complete principle of an LDR is as follows. In a semiconductor an energy gap exists between conduction electrons and valence electrons. As an LDR is also known as semiconductor photo-conductive transducer, when light is incident on it, a photon is absorbed and thereby it excites an electron from valence band into conduction band. Due to such new electrons coming up in conduction band area, the electrical resistance of the device decreases.
3.2SERVER SECTION:
This section describes about server section. The below fig.9. Shows the block diagram of the server section.
Server section contains LPC2148 microcontroller, ZIGBEE module, GPRS/GSM modem, personal computer and power supply circuit. The design of this proposed system is explained as follows.
Fig.9: Block diagram of server section 3.2.1 GSM TECHNOLOGY
GSM (Global System for Mobile communications) is the technology that underpins most of the world's mobile phone networks. It is a second generation cellular standard developed to cater voice services and data delivery using digital modulation. The GSM platform is a hugely successful wireless technology and an unprecedented story of global achievement and
cooperation. GSM has become the world's fastest growing communications technology of all time and the leading global mobile standard, spanning 218 countries.
It is a set of ETSI standards specifying the infrastructure for a digital cellular service. GSM is an open, digital cellular technology used for transmitting mobile voice and data services. GSM operates in the 900MHz and 1.8GHz bands GSM supports data transfer speeds of up to 9.6 kbps, allowing the transmission of basic data services such as SMS.
3.2.2 GPRS TECHNOLOGY
General Packet Radio Services (GPRS) is a very widely- deployed wireless data service, available now with most GSM networks. It is a packet-based wireless communication service that promises data rates from 56kbps to 114 Kbps and continuous connection to the Internet for mobile phone and computer users. The higher data rates allow users to take part in video conferences and interact with multimedia Web sites and similar applications using mobile handheld devices as well as notebook computers. GPRS is based on Global System for Mobile (GSM) communication andcomplements existing services such circuit switched cellular phone connections and the Short Message Service (SMS). The below fig.10 shows GSM/GPRS modem.
Fig.10: GSM/GPRS modem
IV. WORKING OF THE PROPOSED SYSTEM
Automation for Smart Homes with WSN and GPRS TechnologyConsists of two working modes.The WSN system provides means to store information, monitor the sensors placed in smart home, send tasks of the user and monitor the tasks execution by the robot.
(i) AUTONOMOUS MODE
Each room under monitoring deploys several fixed sensors, which is responsible for day-to-day information collection and reporting alarm when something emergency happens [5]. The home server analysis the site information and give the data to user for making decisions. When the accident occurs, the robots take the appropriate action. A camera is used to provide a view of the smart home. Camera may cover a part of the room. Cameras are turned off in normal conditions to reduce unnecessary power consumption. At the time of the event or accident, the camera nodes focusing on the
position of accident and send the pictures to the security cabin. GSM MODEM is used to send the SMS to the owner in emergency case.
(ii) USER CONTROL MODE
Users can control the robot by PC and perform the operation told by user. RFID reader is used to provide the service for door open system in user mode.
4.1 WORKING OF A SERVICE ROBOT
Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks [6]. In this section, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called ‘‘A Line in the Sand’’ and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services.
We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of this work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effectsof network unreliability on application performance.
V. CONCLUSION
In this paper we describe the architecture and implementation of a smart environment with WSN and service robot, in which the home server acts as an intelligent collaborator between our mobile service robot and the environment. To demonstrate the practicability of a WSN and service robot assisted smart home environment, we came up with devices required to provide reliable services, developed them, and implemented software for management and control. The goal of our project is to show the usability of the service robots in our daily lives by constructing the smart environment for the service robots. This attempt is expected to enable humans to focus on the important tasks by liberating ourselves from unpleasant daily chores with the help of services robots. Future work will focus on improvement of above proposed work and adding features to make a reliable smart home system.
REFERENCES
[1] Soares, S.G., Tak a o, T.B., da Rocha, A., Ara u jo, R.A.M., and Barbosa, T.A.: Building Distributed Soft Sensors, International Journal of Computer Information Systems and Industrial Management Applications, 2011, 3, pp. 202-209.
_______________________________________________________________________________________________
[2] Sharma, U., and Reddy, S.: Designof Home/Office Automation using Wireless Sensor Network, International Journal of Computer Applications, 2012, 43(22), pp. 46-52.
[3] R. Szewczyk, A. Mainwaring, J. Polastre, D.
Culler: An analysis of a large scale habitat monitoring application, Proceedings of the Second ACM conference on Embedded Networked Sensor Systems (SenSys), 2004,pp.214–226.
[4] Iniewski, K., Siu, C., Kilambi, S., Khan, S., Crowley, B., Mercier, P., and Schlegel, C.: Ultra- low power circuit and system design tradeoffs for smart sensor network applications, in Editor (Ed.)
Ultra-low power circuit and system design trade- offs for smart sensor network applications,2005, pp. 309-321.
[5] LI Li, LIU Yuan-an, TANG Bi-hua: SNMS: an intelligent transportation system network architecture based on WSN and P2P network,”
The Journal of China universities of posts and telecommunications, 2007, 14(1) pp. 65-70.
[6] A.Arora, P. Dutta,S. Bapat, V. Kulathumani,H.
Zhang,V. Naik, V. Mittal, H. Cao, M. Demirbas, M. Gouda, Y-R. Choi. : A wireless sensor network for target detection, classification, and tracking, Computer Networks (Elsevier), 2004, 46(5), pp.605–634
