Home Security System HSS Computer Science Essay

Security is a serious issue in today 's endeavor environment. The offense rate is increasing due to the successful efforts made by interlopers and hackers. In today 's life, people are busy catching up their tight agenda and it is common to go forth house unattended [ 2 ] . Rapid growing of computing machine control engineering and electronic information, led to an thought of intelligent place. Safe place engineering enables the user to pull off house remotely and improves the comfort of life. When you are in holiday, these systems will direct you watchful messages and supply immense aid at times of exigency.

These systems are capable of supplying light control, heat control and security.

In this article we will take an in-depth expression at assorted security mechanisms of smart house. We chiefly deal with mechanisms like perimeter-based, GSM/GPRS, image processing & A ; 3G based, automatons based on detector web, nervous webs utilizing radio LAN, Bluetooth and ZigBee engineerings.

Bluetooth engineering which is used to pass on control is found to hold disadvantages like high power ingestion and high cost.

Get quality help now

Writer Lyla

Verified writer

Proficient in: Computer Science For Progress

5 (876)

“ Have been using her for a while and please believe when I tell you, she never fail. Thanks Writer Lyla you are indeed awesome ”

+84 relevant experts are online

Hire writer

Latest ZigBee engineering is used to get the better of these jobs as it can set devices at decreased degree of functionality [ 9 ] . They are sent to kip and wake up provinces as per the bids given to them, which in bend save power.

Perimeter-Based attack:

Successful execution of non-functional demands like public presentation and security by a place security system is indispensable. In order to accomplish both of these non-functional demands, perimeter-based place security system is implemented [ 6 ] .

The different types of HSS used are Wed-Based System ( WBS ) , Passive System ( PS ) , Phone-Based System ( PBS ) and Hardware-Based System ( HBS ) . In this perimeter-based attack, the house is divided into different margins and different HSS is applied in each margin in order to accomplish non-functional demands [ 6 ] .

The house is divided into three margins. They are viz. P1 includes extremely valuable countries of place like office room, sleeping rooms ; P2 includes the staying country inside the house and P3 includes the staying country outside the house [ 6 ] .

Fig 1: Perimeter-Based Security for the house [ 6 ]

HBS, WBS is implemented for P1 and P2 severally. PBS and PS are implemented for P3 [ 6 ] .

Hardware-Based System:

HBS ensures high security and gives least control to the proprietor as it is used to guard valuable countries in the place. Equally shortly as detectors are triggered, this system takes determination quickly by triping actuators without informing the proprietor [ 6 ] .

Fig 2: Hardware Based System [ 6 ]

Web-Based System:

The two of import constituents of WBS are web waiter and place accountant. Home accountant is wirelessly connected with sound, door and gesture detectors [ 6 ] . When any of these detectors are triggered, so dismay is generated. The cause of the dismay is captured by the camera and can be viewed by the proprietor on web browser of any device like laptop, phone and personal digital helper [ 6 ] . This is how WBS is said to supply better control to the proprietor.

Fig 3: Web-Based System [ 6 ]

Passive System:

When person tries to open the door, the detector associated with the door is triggered. The place dismay connected to the door detectors will do a call to independent monitoring bureau or proprietor utilizing public switched telephone web [ 6 ] .

Fig 4: Passive System [ 6 ]

Phone-Based System:

This is same as inactive system. But independent monitoring agents or proprietors can corroborate if it was a false dismay or true one utilizing phone web. They can utilize the X10 protocol by telephone accountant to turn the out-of-door visible radiation on [ 7 ] . If this switches on the light sensor that is present indoors, door detector is triggers the dismay once more [ 6 ] . By this they can corroborate that the initial dismay is non false.

Fig 5: Phone-Based System [ 6 ]

All these four types of HSS can be summarized utilizing the below tabular signifier.

Table 1: Different HSS types [ 6 ]

GSM/GPRS based attack:

The demand for low power ingestion and low cost led to the design of Global System for Mobile Communication/ General Packet Radio Service ( GSM/GPRS ) . This includes two parts. They are viz. , wireless security detector nodes and GSM/GPRS gateway [ 8 ] .

The chief characteristics of GSM/GPRS are low cost, low power ingestion, easy installation, rapid response, friendly user interface, information security method and exigency dismay map [ 8 ] .

Fig 6: Structure of the system [ 8 ]

GSM/GPRS gateway and web are connected via GSM/GPRS faculty [ 8 ] .

This system uses 8-bit PSoC ( Programmable System on Chip ) microprocessor. The chief intent of utilizing this bit is, it is easy to plan, low cost, low power ingestion and reduces the design complexness [ 8 ] .

Fig 7: GSM/GPRS gateway [ 8 ]

Microprocessor I receives security information from security nodes through transceiver faculty. It displays alarm information on LCD and sends out alarm messages to remote users via GSM/GPRS faculty [ 8 ] . Microprocessor II receives the keyboard information and sends it to microprocessor I through consecutive peripheral interface [ 8 ] .

GSM/GPRS consists of three wireless security detector nodes. They are viz. , infrared security nodes, door security nodes and fire dismay nodes [ 8 ] .

Door Security Node:

This security node does non necessitate external power supply as it adopts magnetic detector. It has ON/OFF signal and its end product depends on the distance between the magnet and dry spring [ 8 ] .

Fig 8: Door security node [ 8 ]

Infrared Security Node:

This detector is placed in different countries like entrywaies of room. If an interloper enters, detector will observe the infrared radiation generated by the interloper as the node adopts pyroelectric infrared detector. The end product generated is a little signal and it should be processed. By utilizing microprocessor which is configured of amplifier, filter and parallel to digital convertor is used to treat the signal, thereby cut downing power ingestion [ 8 ] .

Fig 9: PIR detector [ 8 ]

Fire Alarm Node:

This security node comprises of temperature detector and infrared receiving system. Temperature detector is responsible of supervising environment temperature and infrared receiving system is responsible for feeling heat and fires. When these detectors detect that the environment exceeds the defined threshold values, so this node sends out an alarm signal [ 8 ] .

Image processing and 3G based attack:

For cut downing false dismay rates and to hold recorded grounds of offense for later review, image processing and 3G communicating engineering is proposed [ 10 ] . It achieves this based on ARM9 engineering, S3C2410 hardware platform and embedded Linux OS.

The system includes door, infrared, fume and gas detectors. In instance of exigency CPU receives a admonitory signal and it determines the type of dismay. It controls the camera to the gaining control picture images and shops them in buffer. Embedded platform will preprocess the image informations which is converted into file format and this user datagram protocol ( UDP ) package is sent through 3G to the user [ 11 ] . This is how the proprietor uses 3G to manage the state of affairs at place.

Fig 10: System 's working rule [ 10 ]

Fig 11: System hardware design [ 10 ]

ARM maestro faculty:

Arm is the chief faculty which controls dismay input & A ; end product I/O ports, receives and conveying picture informations and 3G web communicating. It constitutes 64MB high-velocity dynamic entree memory [ 10 ] . The bit S3C2410 consumes low power and has high public presentation.

Video processing faculty:

For picture processing Video4Linux is used which provides interface maps for video equipment maps.

Alarm input and end product circuits:

The dismaies and sensors are connected to the accountant through General Purpose Input/ Output ( GPIO ) . The system uses photoelectric isolation bit TLP521 to cut down the high power impact of the equipment on the system [ 10 ] .

This 3G based system has characteristics such as low cost, high dependability, low loss, provide picture grounds, high public presentation and can cut down false dismay rate.

Home security system utilizing nomadic automaton and detector web:

A Sensor web based Home Security system ( HSSN ) has been proposed which is configured by detector nodes including wireless frequence ( RF ) , supersonic, temperature, visible radiation and sound detectors [ 1 ] .

This system consists of Home Security Mobile Robot ( HSMR ) , Home Server ( HS ) and Sensor Network ( SN ) that is configured by Cricket nodes ( CN ) [ 1 ] .

Architecture of the system:

Fig 12: HSSN system architecture [ 1 ]

HS uses RF and radio LAN to have and convey place security information. When it receives alarm event information, it transmits event log message to user interface device ( UID ) [ 1 ] . At this point of clip, based on the information of each detector node nomadic automaton follows optimum trajectory way and reaches the dismay zone ( AZ ) . Then HSMR captures the current context-aware images of dismay zone and transmits so to the user through HS [ 1 ] . This is how the user recognizes his place security. The communicating among these units of the system is through RF indoor and radio LAN outdoor.

Fig 13: HSSN system process [ 1 ]

In SN there are three system operation manners. They are viz. , Event Sensing Mode ( ESM ) , Communication Mode ( CM ) and Home Security Activation Mode ( HSAM ) [ 1 ] .

The two processs in HSSN system are Security Mode Transition Procedure ( SMTP ) and HSSN Activation Procedure ( HSSNAP ) [ 1 ] .

In SMTP, HS receives context-aware information in hop-by-hop through RF from a CN which detects an alarm event from a detector faculty. Then HS sends event log message to remote user and informs him about the place security information. At this point of clip, all CNs transportations into CM from ESM as radio communicating have to be initialized [ 1 ] . At the terminal of this process, all CNs transportations into HSAM from CM as per the bids given by HS. During this full process all CNs activate RF and supersonic detectors.

While in HSSNAP, with the aid of instructions from HS mobile automaton plans an optimum flight and reaches the finish. It so captures context-aware images and sends so to HS. HS eventually integrates the information that it receives from all CNs and nomadic automaton and sends them to the distant user utilizing wireless LAN [ 1 ] . This helps the user to react when his house is in unsafe context.

Functions of Sensor web, Home waiter and Mobile automaton:

Sensor web:

The MTS310CA sensor board is equipped with sound, temperature and light detectors. The CN transmits context-aware information which it acquires through the sensor board [ 1 ] .

Sensor faculty holding sound, visible radiation and temperature detectors are added on the cricket faculty [ 1 ] .

Fig 14: Cricket hardware unit and detector board [ 1 ]

Home waiter:

Home waiter is the bosom of the full system. Based on the information received from CNs and HSMR, HS is capable of finding assorted security state of affairss like sound, invasion, fire, light and many more [ 1 ] . HS receives information about invasion and gas sensing through wired detectors. HS communicates with UID, Sensor Network and HSMR by radio LAN, RF and Bluetooth [ 1 ] .

Fig 15: Wireless communicating among HS, HSMR and Personal Digital Assistant ( PDA ) [ 1 ]

The user interface screen of Personal Digital Assistant ( PDA ) is shown in Fig 5.

Fig 16: User interface screen on PDA [ 1 ]

Mobile automaton:

In this system, both triangulation algorithm and dead-reckoning method are used to cipher the absolute and comparative places of the nomadic automaton. For avoiding obstructions and for obtaining optimum way, detectors are besides added to mobile automaton.

HSMR undergoes three methods. They are viz. , Triangulation, Dead-Reckoning ( DR ) and Path-Planning.

In triangulation, nomadic automaton uses RF and supersonic signal to happen the absolute place and distance from the Cricket nodes [ 1 ] .

Dead-Reckoning is a procedure in which comparative place of nomadic automaton is determined utilizing two optical encoders and one electric compass [ 1 ] . Several steps are taken to cut down the localisation mistake.

Fig 17: Triangulation and Dead-Reckoning procedure [ 1 ]

For way planning, both HS and HSMR portion the same place map tabular array ( HMT ) . Mobile automaton moves harmonizing to the correlativity between HMT and the mark place.

Fig 18: Way planning [ 1 ]

Nervous Network attack:

Most of the security mechanisms provided by smart place deficiency the intelligence for high determination devising. This may take to doing false dismaies. Furthermore the environment of each smart place varies from topographic point to topographic point and from state to state [ 2 ] . So in such instance, predefined security instructions may non work good. There arises a demand for smart place that can follow an intelligent algorithm with self-learning capableness [ 2 ] . Intelligent algorithm such as nervous web is capable of measuring the environment and taking necessary determinations.

There are some bing jobs that the security systems fail to verify. When the resident existed in the house, he will demilitarize the detectors in the house. So there is no security when the dweller existed in the house [ 4 ] . Frequent happening of false dismay would cut down the efficiency of exigency response. Most of the security systems take long clip to respond to the triggered dismay and there is a range for the interloper to get away [ 5 ] . This is because these systems have no intelligence in judging the state of affairs and placing false dismay. Therefore the demand for nervous web has been recognized in smart place for informations analysis.

As preparation period is long utilizing Backpropagation Neural Network ( BPN ) , nervous web is trained utilizing resilient backpropagation algorithm ( RPROP ) [ 3 ] .

The preparation phase of nervous web:

Passive infrared ( PIR ) , closed-circuit telecastings ( CCTV ) , radio-frequency designation tickets ( RFID ) and readers, magnetic contacts, glass breakage detectors, the clip when detectors triggered is fed as input to gesture detectors [ 2 ] . As numerical information is the lone informations type that is accepted by nervous web, the above input values are converted into numerical informations utilizing convertor [ 2 ] . Later the nervous web is trained via concealed nerve cells and the end product of this would be intruder detected or non detected. The coveted consequence is compared with the existent consequence and concealed nerve cells are adjusted to better the system 's truth. This procedure is repeated iteratively on 100s of dataset to increase the hardiness of the system [ 2 ] .

The figure below shows the assorted stairss involved in developing stage of nervous web.

Fig 19: Training phase of Neural Networks [ 2 ]

Cross-Validation phase of nervous web:

This phase helps to measure the preparation public presentation of the nervous web and halt the preparation if needed [ 2 ] . The coveted end product is compared with the existent end product to mensurate the public presentation. If the public presentation of the system is good, preparation is stopped or else it is trained with the following dataset.

Fig 20: Cross-Validation phase of Neural Network [ 2 ]

Testing phase of nervous web:

After completion of preparation and cross-validation stages, the nervous web is tested with a new dataset from existent universe scenario. The end product of the system is compared with human being 's consequence and later it is used as existent universe security system if it is proved to work good [ 2 ] .

Fig 21: Testing Phase of Neural Network [ 2 ]

Decision: