Design of intelligent sensor based on BP neural network and ZigBee wireless sensor network

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1 Avalable onlne Journal of Chemcal and Pharmaceutcal Research, 204, 6(6): Research Artcle ISSN : CODEN(USA) : JCPRC5 Desgn of ntellgent sensor based on BP neural network and ZgBee wreless sensor network Yun Wang # and Kunpeng # College of Computer and Informaton Engneerng, Xnxang Unversty, Henan Xnxang, Henan College of Fnance & Taxaton, Henan Zhengzhou, Chna ABSTRACT Intellgent sensor s a sensor n addton to the basc functon, zero, self calbraton, self calbraton and has the functon of automatc adustment, along wth logc udgment and the ablty of nformaton processng, can be a measurement sgnal condtonng or sgnal processng. Multlayer BP neural network s a one-way transmsson of feedforward network, and t uses the error output estmaton error drectly leadng layer to output layer, and then the error estmaton error of a layer. The paper proposes desgn of ntellgent sensor based on BP neural network and ZgBee Wreless Sensor Network. Experments show that the proposed ntellgent sensor has hgher effcency. Keywords: BP neural network; ZgBee; Wreless Sensor Network; Intellgent sensor. INTRODUCTION In ZgBee network, the physcal devce supports two types of, full functon devce (Full Functon Devce, FFD) and reduced functon devces (Reduced Functon Devce, RFD). Full functon devce (FFD) support all topologcal structure, can be used as a network coordnator (Coordnator) can also be used as a routng node and termnal sensor node, wth the functon of the controller; reduced functon devces (RFD) can transmt nformaton to FFD or from FFD to receve nformaton. Wreless sensor network node generally conssts of a sensor module, data processng module, data transmsson module and power management module s composed of four parts []. The sensor module s responsble for collectng the montored area nformaton and complete the data converson, acquston of nformaton can nclude temperature, humdty, lght ntensty, acceleraton and atmospherc pressure; data processng module s responsble for the control of the node processng operaton, routng protocol, synchronous postonng, power management and task management; data communcaton module for wreless communcaton wth the other nodes exchange control messages, and send and receve data. BP neural network s a knd of three or more than three layers of neural network, ncludng nput layer, mddle layer (hdden layer and the output layer). The connecton between the upper and lower, and t s between each layer of neurons wthout connecton. When a par of learnng samples provded to the network, neuron actvaton values from the nput layer to the output layer of the mddle layer of communcaton, network nput response n each neuron n the output layer [2]. Next, accordng to reduce the target output and error drecton, from the output layer after each mddle layer gradually modfy connecton weghts, and fnally back to the nput layer, ths algorthm s called "error back propagaton algorthm, namely BP algorthm." The ntellgent sensor has strong real-tme performance; especally the dynamc measurement often requres data acquston, calculaton, processng and output wthn a few mcroseconds. A seres of smart sensor are carred out under the support program. Such as the functon of how much, basc performance, convenent use, relable work, 820

2 mostly n a certan extent depends on the software desgn and the qualty of the software; there are fve man types of t. Includng the scale converson, dgtal adustable dgt zero, and t s nonlnear compensaton, temperature compensaton, flterng technology. The paper proposes desgn of ntellgent sensor based on BP neural network and ZgBee Wreless Sensor Network. 2. Usng ZgBee Wreless Sensor Network to Buldng Intellgent Sensor ZgBee wreless communcaton technology s a new short dstance wreless communcaton technology, wth low power consumpton, low rate, low delay and other characterstcs, has a strong network capablty and large network capacty, can be wdely used n consumer electroncs, home furnshng and buldng automaton, ndustral control, medcal equpment and other felds. Because of ts unque characterstcs, the preferred technology of ZgBee wreless technology and wreless sensor networks, wth broad prospects for development. ZgBee protocol uses the open system nterface (05) herarchcal structure, the physcal layer and meda access layer by the IEEE workng group to develop, and the network layer, securty layer and applcaton framework layer by the ZgBee allance establshment. Although W-F transmsson speed can reach Mbps, the transmsson dstance can reach 00 meters, but ts prce s expensve relatve to teach, and large power consumpton, poor network ablty. ZgBee technology focuses on the low cost, low power consumpton and low rate wreless communcaton market, so t s very sutable for the applcaton n the Internet of thngs n wreless sensor networks. The ntellgent sensor has a sensor nformaton processng functon [3]. Intellgent sensor wth mcro processor, has the ablty of collectng, processng, exchange of nformaton, s a product of ntegrated sensor and mcroprocessor combnes. The sensory system ntellgent robot conssts of multple sensor assembled, collectng nformaton to the computer for processng, whle the use of ntellgent sensor can be decentralzed nformaton processng, thereby reducng costs. Compared wth the general sensor, ntellgent sensor has the followng three advantages: through software technology can realze the nformaton acquston of hgh precson, and low cost; has the certan ablty of programmng automaton; functonal dversty. The number of external components CC2430 rarely, t uses non balanced antenna, because the connecton of non balance transformer can make better the performance of the antenna. Current CC2430 wreless mcrocontroller n the standby power consumpton s only 0.2 µ A, current operatng at 32 khz crystal clock when the consumpton of less than µ A. Therefore, the use of small battery lfe can be as long as 0 year. The ZgBee protocol uses herarchcal structure; each layer layer provdes a seres of specal servces: data entty provdes data transmsson servces; management entty provdes all other servces. SAP servce access pont SAP layer provdes nterfaces; servce prmtves are supported by every SAP number to acheve the desred functon. The herarchcal archtecture of ZgBee standard s based on OSI seven layer models accordng to the actual need to defne on the market and applcaton. Router manly realze the expanson of network and routng messages, as the parent node n the network s potental, allowng the devce to access the network more, routng nodes can only exst n a tree network and mesh network. The termnal equpment s the edge nodes of the network s connected wth the montorng obect, s responsble for the actual, the devce only wth ther parent node actve communcaton, nformaton routng specfc all turn coordnator and router by ts parent node and network wth routng functon completed. Each node s usually an embedded system, has collected data, recevng the order, processng of data, and recevng wreless data transmsson, processng power, storage capacty, communcaton ablty of each node s relatvely lmted. The sensor node s desgned n ths paper the realzaton mechansm s seral communcaton module wth IEEE/ZgBee transmsson module to replace the tradtonal, nformaton wll be collected data wrelessly sends out. The node also package IEEE/ZgBee wreless communcaton module, mcrocontroller module, the sensor module and nterface, DC power supply module and an external memory. Wth P4_5 O, the CE sgnal n low level, and chp select K9F208 effectve; gven P4_4, the CLE sgnal nto a hgh level, so that the K9F208 command allows sgnal effectvely; wth P4_3 O, the ALE sgnal n low level, so that the K9F208 addresses allow sgnal wthout effect; the last empty wrte command the word of rk9f208data, makes the WE sgnal n low level, the K9F208 command regster to receve from the data bus to the command word, and perform the approprate acton. The nodes of wreless sensor network are composed of a software layer and hardware layer together to acheve functonal [4]. Constructon of wreless sensor network n the applcaton of ZgBee chp, ZgBee chp hardware 82

3 bult-n part of the functon of physcal layer and MAC layer, other top settlement outsde of MPU, by wrtng to the MPU, to acheve the ZgBee protocol. Fgure s the nternal structure of graph nodes. Node applcaton part devce accordng to dfferent poston control (such as temperature, sound, vbraton, pressure, moton or reducng pollutants) play a dfferent role. The devce s very small, very cheap, mass-produced and deployment, so ther resources (energy, storage, computaton speed and bandwdth) lmted. Each node has a wreless "> rado transcever, a very small mcro controller and an energy (usually battery). These devces to help each other and t are to transfer data to a computer. Fg.. Constructon of wreless sensor network n the applcaton of ZgBee chp The ntellgent sensor has strong real-tme performance; especally the dynamc measurement often requres data acquston, calculaton, processng and output wthn a few mcroseconds. A seres of smart sensor are carred out under the support program. Such as the functon of how much, basc performance, convenent use, relable work, mostly n a certan extent depends on the software desgn and the qualty of the software; there are fve man types of. Includng the scale converson, dgtal zerong, nonlnear compensaton, and t s temperature compensaton, dgtal flter technology. The IEEE standard on-chp uses ZgBee products. CC2430 usng the latest SmartRF03 technology and 0.8 µ mcmos process, and t s usng 7 7 mm QLP48 package. The chp ncludes RF transcever, also ntegrates enhanced 805MCU, 32 / 64 / 28 KB Flash memory, 8 KB RAM, ADC, DMA and watchdog. CC2430 works n the 2.4GHz band, wth low voltage (2 ~ 3.6 V) power supply, and the power consumpton s very low (27 ma when recevng data, send data for 25 ma), hgh senstvty (-97 dbm), the maxmum output s 24dBm, the maxmum transfer rate of 250 KB / s. When the seral data nto the XBee Pro module through the DIN pn, the data wll be stored n the DI buffer, untl t s sent out by the antenna transmtter; when the antenna receves RF data, receve data frst enters the DO buffer, and then sent to the host seral. Under certan condtons, the module may not be able to process on the data n the recevng buffer mmedately, ths tme on the need to CTS flow control n order to avod recevng buffer overflow problem caused by the large number of seral data nput. XBee Pro module through UART nterface s drectly connected wth the UART nterface controller, the hardware nterface s very smple and practcal. In ths paper, called the multple subroutne modules s used to process the correspondng functon. Intalzaton module to ntalze the system and ZgBee module, frequency of the system to ensure the normal work of the RF oscllator frequency at 32 MHz; the nformaton query module to query the nearby communcaton node; communcaton lnk module s used to establsh the data lnk montorng regon between the nodes; data communcaton module s used for recevng and analyss to the wreless sensor network node the data nformaton, processng data nformaton s sent out. Zgbee data acquston module nstalled on the unt s buldng one layer or more convenent meter readng meter readng poston. When the Zgbee module to receve data through the LED drver chp data output to the LED dsplay, so the meter readng personnel can clearly readng, of whch the frst two used to dsplay the occupants of the room, after sx used to dsplay water meter data correspondng to the room number. The keyboard s used to control the LED dsplay. Among them, the ntellgent keyboard and LED drver and USB drver chp RIC6C63 and 822

4 USBN9602 chp were used. Zgbee network protocol, each node has two addresses: 64 IEEE MAC address and 6 bt network address. Each one usng Zgbee protocol communcaton devce has a unque 64 bt MAC address, the address s 24 bt OUI and 40 bt manufacturers address allocaton, by OUI buy assgned by IEEE, snce all of the OUI are specfed by IEEE, so the 64 IEEE MAC address wth a global unqueness [5]. When the devce s executng ons the network operaton, they wll use the extended address ther communcaton. Successful entry nto the Zgbee network, the network wll be assgned a 6 bt network address to the equpment. Thus, the equpment can be used n other devces of the address and the network of communcaton, as s shown by equaton. STD= M N = 0 = 0 2 ( F(, ) MEAN) /( M N) () ZgBee can use satellte, sheet and mesh network structure, whch s composed of a man node management of a number of chld nodes, up to a master node can manage 254 chld nodes; at the same tme, the master node can also be composed of a layer of network node management, most can be composed of node network. ZgBee provdes three levels of securty, ncludng non securty settngs, use access control lst (ACL) to prevent llegal access to data and the use of Advanced Encrypton Standard (AES28) symmetrc cpher, wth flexble and determne ts safety propertes. Zgbee2007, Zgbee2006, DIGIMESH. The effectve range wth the settng module s automatcally added to the network, and data communcaton wth an arbtrary module network. Advantages are: module automatc networkng, ths dstance can be extended. All the modules are a common type (outdoor vsblty range 00M) and enhanced (outdoor room dstance.6km) two f need farther module, you can also use DIGIXtend products (dstance to reach 64KM). Intellgent sensor s a sensor n addton to the basc functon, zero, self calbraton, self calbraton and has the functon of automatc adustment, along wth logc udgment and the ablty of nformaton processng, can be a measurement sgnal condtonng or sgnal processng. In ndustral producton, not for some product qualty ndex by usng the tradtonal sensor (e.g., vscosty, and t s hardness, surface roughness, composton, color and taste etc.) for rapd drect measurement and onlne control. A certan amount of producton process and usng the functon relatonshp between ntellgent sensor can drectly measure and product qualty ndex of (such as temperature, pressure, flow, etc.) are calculated by use of the establshed mathematcal models of neural network and expert system technology, can be nferred from the qualty of the products. 3. Usng BP Neural Network to Constructon Intellgent Sensor BP (Back Propagaton) neural network, namely the error back propagaton error back-propagaton learnng process, the reverse forward propagaton and error propagaton conssts of two processes. The nput layer of each neuron receves nput nformaton from the outsde world, and passed to the neuronal ntermedate layer; the mddle layer s the nternal nformaton processng layer, s responsble for the nformaton transform, accordng to the ablty of nformaton demands, the mddle layer can be desgned as sngle hdden layer and hdden layer structure; the last hdden layer transfer to the output layer neurons nformaton, after further treatment, complete forward propagaton process of a learnng, the output layer the outsde world to output the results of nformaton processng. The neural network s learnng or tranng. The so-called tranng, s n the sample set (or called the tranng set) nput to the process of the neural network, accordng to certan rules, connecton weghts adustment between neurons, so that the network can store the relatonshp between sample set n the connecton weght matrx way, whch makes the network to accept nput, to gve the approprate output [6]. Learnng s one of the most mportant functons of neural network. Neural network s through contnuous smulaton and learnng of the neural network, the smulaton results and performance error change curve correcton network parameters fnally get the weghts of the network, an optmal threshold value and other parameters. Neural network evaluaton of changng network parameters s the bass of learnng rules. The learnng rule of neural network s generally dvded nto supervsed learnng, unsupervsed learnng two rules. Ths paper desgns a BP network, the followng functon approxmaton formula 2: mplementaton of the nonlnear functon approxmaton. Among them, 2, 4 respectvely, k=, smulaton, by adustng the parameters (such as the hdden layer node number of hdden layer nodes) that frequency and sgnal, the relatonshp between the hdden 823

5 layer nodes and functon approxmaton ablty. g(x)=+sn(k*p/4*x) (2) Neural network s obtaned by applyng a seres of neurons connected together, s a knd of nterconnecton system complex, nterconnected model varety, manly has the followng several types:, to the network, feed forward network, each layer of neurons receved only a layer of neurons n the nput, output and no relatonshp wth neuron layer and the next layer, also won't gve the front layer transmts a sgnal feedback. Input sgnal through layer s by layer sequence mode converson, and ultmately by the output layer. 2, the feedback network n feedback network, from the output layer to the nput layer wth sgnal feedback, make adustment feedback on the nput of network weghts and threshold, to mprove the performance of network learnng. RBF network has the advantages of smple structure, smple tranng, and ts learnng convergence speed, can approxmate any nonlnear curve, and has the unque characterstcs of best approxmaton, and have no local mnma; but the RBF neural network, how to choose the approprate radal bass functon, how to determne the number of hdden layer neurons, n order to make the network learnng to ask precson, at the same tme, hdden layer neuron center s hard to fnd, these are the mportant reasons causng the RBF neural network s wdely used. Wth the error back propagaton correcton unceasngly, network to the correct nput mode response rate rsng. Wth approprate parameters, network convergence to have a smaller varance. BP neural network s as the most basc three layer feedforward network, ncludng nput layer, hdden layer and output layer. Fgure 2 shows the prncple of BP neural network structure dagram. Fg. 2. The prncple of BP neural network structure dagram In order to support the nformaton processng model, there are three mportant technologes s formed and fuson, whch s a wreless sensor network, low power embedded computer and ntellgent sensor. The computer and the ntellgent sensor technology are developng quckly and relatvely mature. Wreless sensor network s stll n the formaton. In order to provde perceved envronmental condton to the workers, we must construct the model, mplementaton of nfrastructure wreless ntellgent sensor network based on. Constructon of percepton envronment usng wreless sensor network has a bult-n ntellgent sensor - regardless of whether the user can obvously feel the - called smart sensor. Dynamc response of capactve sensors due to the electrostatc attracton between the plates s small, energy need mnmal, because the movable part of t can be very small, very thn, the qualty s lght, so the natural frequency s very hgh, dynamc response tme s short, can rate work n a few THz frequency, especally sutable for dynamc measurement. And because of ts delectrc loss s small, can use hgh frequency power supply, so the system works n hgh frequency. It can also be used for the measurement of rapd change. Intellgent sensor market growth makes the ntellgent sensor standard emerge as the tmes requre. The IEEE45 standard defnes a standard transducer nterface module (STIM), of whch, ncludng sensor nterface, sgnal condtonng and converson, calbraton, lnear and network communcaton. In essence, the standard for ntellgent sensor wth plug and play functon, ths can be connected to the ntellgent sensor network. The standard s composed of IEEE 45., 45.2, P45.3 and P45.4. At present, the new IEEE45.5 (wreless sensor communcaton nterface standard) formed the contenton of a hundred schools of thought wth the stuaton of the ZgBee allance, Z-Wave allance, Wreless USB sensor networks. 824

6 In BP network, as long as the proper hdden layers and hdden nodes, the nonlnear mappng relatonshp between BP networks can approxmate arbtrary, and BP algorthm s a global approxmaton method, has good generalzaton ablty [7]. The so-called generalzaton ablty refers to the ablty of neural network for fresh samples. Usually expect the tranng samples to tran the network has good generalzaton ablty; also s the ablty to gve a reasonable response of the new nput. Defcency of BP network s the BP algorthm takes a long tranng tme, slow convergence, and s easy to fall nto local extremum, determne the number of hdden layer and hdden node number has been no better method, as s shown by equaton(3). E E E Net ( k) δo( k) = ; = Net ( k) w Net ( k) w (3) Where ths error functon a =, w = x p p E( k) = 2 p u= 2 [ d ( k) y ( k)] k =,2, L, N, and note: p Net ( k) = θ w = and, the sample number (number of samples). The network layer node number of nput and output layer nodes need accordng to the specfc problem analyss. The nput layer neurons may accord need to solve problems and data representaton method to determne. Nodes n the output layer accordng to the user requrements to determne the node s needed, the predcted results obtaned contans number. The selecton of the hdden layer nodes s a very complcated problem. There s a hdden layer of the neural network, as long as the number of hdden layer node s enough, can approxmate any nonlnear functon. 4. Desgn of Intellgent Sensor based on BP Neural Network and ZgBee Wreless Sensor Network Intellgent sensor parameters may be vared. But the composton from the functon module, t manly ncludes data acquston module, compensaton and correcton module, data processng module, data communcaton module, man-machne nterface and task management and schedulng module and other functonal unts. Thus the ntellgent sensor SOC desgn process based on IP: unversal module model s frst establshed ntellgent sensor; then dvde each module functon specfcaton, makng the nterface protocol between modules and standard; then desgn a seres of general purpose IP nuclear; fnally the requred common IP nuclear buld together consttute the ntellgent the complete sensor system. In wreless sensor networks, FFD s forwardng and routng capabltes have enough storage space to store routng nformaton, and the processng ablty to control the correspondng enhancement. ZgBee also supports thrd knds of nodes, namely network host or gateway nodes, routng and to external system nterface or coordnaton wth other networks. FFD sometmes play the role of the gateway. A network requres only a network coordnator, other devces can be RFD, also can be FFD. RFD prces are much cheaper than the FFD, the system resource occuped only about 4 kb, and therefore the overall network cost s relatvely low. W And gven all the weghts, ntal ( I =,2, L, p; =,2, L, q; h =,2, L, n); n, p, q and neuron threshold values were layer unt number. The correspondng number unt nput layer by K s sample S k)[ s ( k) s ( k) s ( k)] n ( 2 L value ; as the actvaton value unt values for the followng formula 4. T (k ) s h, the weght matrx V, the A s actvaton of each, a ( k) = f( n v s ( k) + θ ) = f( h h h= n v s ( k) + θ ( k)) h h k= (4) The number of external s components CC2430 lttle. It uses a non balanced antenna, non balance transformer connected to better the performance of the antenna. The non balance transformer crcut composed of the capactor C9 and the nductor L, L2, L3 and a PCB mcrowave transmsson lne, the whole structure to meet the matchng resstor RF nput / output (50 ohms) requrements. Exchange of nternal T/R swtchng crcut s between LNA and PA. R, R2 bas resstor. The R s manly used to provde workng current sutable for crystal oscllator s 32 MHz. Wth 32 MHz quartz resonator and two capactors (C, C2) 32 MHz crystal are oscllator crcut. Voltage regulator voltage on all.8 V pns and nternal power supply, Cl0, C2 decouplng capactors are used for power supply flterng. Zgbee remote termnal user module through the decodng mode s to ntellgent data acquston, and then through the module RF transmsson to Zgbee data acquston module. The collected data s sometmes delayed, the man 825

7 reasons may be caused by Zgbee RF part, and therefore, even after a lot of experments, the RF modulaton of Zgbee, the collected data s more accurate. The development of ntellgent sensor s manly dvded nto three stages, namely, the ntellgent dgtal phase compensaton and calbraton stage, ntellgent and network stage. The thrd stage has reached sensor, sgnal detecton and processng, logc udgment, two-way communcaton, closed loop control, self nspecton and self dagnoss, ntellgent correcton and compensaton calculaton, functon, network communcaton and other functons. Wreless sensor network node of the network Zgbee nput feature factor node layer neuron number s the system (varable) number; the output layer neuron node number s the number of target. Hdden layer nodes selected by selectng experence, usually set as nput layer node number 75%. If the nput layer has 7 nodes, node n the output layer, the hdden layer can temporarly set to 5 nodes, whch form a 7-5- BP neural network model. In the tranng, practcal but also on the hdden layer nodes of dfferent number 4, 5, 6 respectvely, fnally determne the network structure of the most reasonable. To determne the ntal weghts, the ntal weghts are not completely equal to a set of values. Have demonstrated, even determne the exstence of a group of non equal the system error smaller weghts, f the ntal set of W values are equal to each other, they wll always reman equal n the learnng process. Therefore, n the process, we desgn a random number generator program, a random number generatng a set of a 0.5~+0.5, as the ntal weghts of the network. The topologcal structure of network layer s responsble for the establshment and mantenance of the network connecton, the man functons nclude mechansm used n equpment connect and dsconnect the network, as well as adopted n the frame nformaton transmsson n the process of securty mechansm. In addton, also ncludes equpment route dscovery and route mantenance and care. And, t s the network layer to complete a ump (one - hop) neghbor devce dscovery and relevant node nformaton storage. A ZgBee coordnator to create a new network, addton of new equpment allocaton short address etc.. And, the network layer s to provde the necessary functons, ensure that the ZgBee MAC layer of normal work, and to provde approprate servce nterface for the applcaton layer. Intellgent sensors and communcaton sub statons bus network, ntellgent sensor as from the machne, the measurement results are sent to the communcaton substaton, the substaton remote transmsson to the montorng computer. Zgbee s used for remote meter readng data by European standards, t has the followng characterstcs: two wre bus, not dvded nto postve and negatve polarty, the constructon s smple; the dgtal sgnal transmsson level features unque, strong ant-nterference ablty; bus can provde a regulated power supply of 3.3v/3ma for each communcaton node, provdng two power supply for nstrument; can use any bus topology structure, system network low cost, flexble expanson. CONCLUSION The paper proposes desgn of ntellgent sensor based on BP neural network and ZgBee Wreless Sensor Network. In ZgBee protocol n applcaton layer s composed of applcaton support sub layer, ZgBee equpment confguraton layer and user applcaton program. The applcaton layer provdes a hgh-level protocol stack management functon, the user applcaton program set by the manufacturer, t uses the applcaton layer management protocol stack. BP network can learn and store a lot of nput - output model mappng, wthout pror to reveal the mathematcal equatons descrbng the mappng relatonshp. Its learnng rule s to use the method of steepest descent, to constantly adust the network weghts and threshold by back propagaton network, the mnmum error sum of squares. REFERENCES []. We LIU; Yuhua YAN. IJACT, 20, 3(5), [2]. Xueun L; Xn L; Lngl Jang; Guangbn Wang; M. Ka Pckavet. JCIT, 202, 7(22), [3]. Yan Wang. JDCTA, 202, 6(2), [4] Janhu Wu; Hongbo Shao; Yu Su; Zhengun Guo. Journal of Chemcal and Pharmaceutcal Research, 204,6(3), [5]. Zhang Geng; Xu Hao; Shan Kefeng. JDCTA, 202, 6(4), [6]. Hua Jang; Jng Yang; Hongle Zhang. IJACT, 202, 4(7), [7] Ye Lu and Rongsheng Lv. Journal of Chemcal and Pharmaceutcal Research, 203,5(0),