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 Monitoring System of Sewerage Treatment based on

Wireless Network

Xianhui Shao*, Xiaowei Liu, Haifeng Zhang

MEMS Center

Harbin Institute of Technology

Harbin, China

e-mail:huihui6007@163.com 

 Abstract  —How to protect the fresh water sources is one of the

principal problems in the human society, and obviously the

industrial sewerage is the main pollution source. However, some

water quality monitoring systems based on WSN have been done;

we found that the traditional WSN nods have a disadvantage of

short-distance communication among the nods, which limits the

application in monitoring the industrial sewerage. In this paper,

we describe a new monitoring system, which is based on the

ZigBee network, the RF front circuit and the dynamic routing, inorder to realize long-distance communication among the nods

and real-time monitoring. This system described is general,

extensible, self-organized and adaptive, with large area overlay

and excellent compatibility.

 Keywords-Monitoring System; WSN; long-distance; ZigBee;

embedded OS

I.  I NTRODUCTION 

How to protect the fresh water sources of the earth andreduce the gross of industrial sewerage has become one of themain issues for the whole world from now to future [1]. Inorder to save the water source, environmental monitoring is

adopted as the most promising technology, via the applicationof the wireless sensor network (WSN) [2][3].

ZigBee is a optimized standard for WSN, which is used inseveral applications such as sensors interconnecting,monitoring and automating different systems in home,hospitals, manufactories and agriculture [4][5]. In recent years,many successful research works have been done in theenvironmental monitoring areas. There are several hardwareand software solutions for implementing monitoring systemsfor the most varied scenarios. But the range of communicationdistance among the nods is usually from 10m to 100m. Thus,the systems referred above are not suitable for the applicationof monitoring the environment around the factories. So, a new

wireless environmental monitoring system based on ZigBee isdesigned, with 1.5km maximal communication distance between two nodes. This new system is self-organized andadaptive with large area overlay.

II.  SYSTEM ARCHITECTURE 

Fig. 1 shows the system architecture, which comprises three basic tiers as described below.

The infrastructure tier: This tier contains the wireless sensornodes and the special sensors for the industrial sewerage

monitoring. For environmental observation, sensor nodes areusually diffused into the certain areas, where the factoriesoutput their waste water. Thus, the sensor nodes can monitorthe water quality or detect the changes of the environment,collect the messages of the environment and send them to theupper tier directly.

The route tier: The route tier is composed of many route

nodes, which belong to different groups. Based upon theinfrastructure tier, the route nodes collect and transmit theinfrastructure tier messages, receive and send the usercommands to the sensor nodes. The route nodes can be alsoorganized in the format of group.

Figure 1. System architecture 

The user tier: As the important part of the monitoringsystem, the user tier collects all the messages from the sensornodes and also sends the commands to these nodes, via theroute tier.

 A.  Hardware Structure

Fig. 2 shows the Hardware structure of the wireless node,which comprises six basic parts. MCU Module, WirelessModule and RF Front Circuit is important.

Figure 2. Hardware structure of the wireless node

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MCU Module: LPC2138 with the core of ARM-7, whichhas 512k flash memory and 32k RAM, is selected as the micro- processor (MCU). The μC/OS operation system (OS) isembedded in the MCU module to realize these functions.

Wireless Module: The CC2530 SoC (System on Chip) is anappropriate solution specifically tailored for IEEE 802.15.4 andZigBee applications. The CC2530 combines an industry-standard enhanced 8051 MCU, 128 KB flash memory, 8KBRAM and combined with the industry leading ZigBee protocolstack (Z-Stack) from Texas Instruments.

RF Front Circuit: Fig. 3 shows the RF front circuitstructure. The best working band at 2.4GHz-2.5GHz low- power linear RF amplifier chipRF5189 is used in RF poweramplifier section. The chip's small-signal gain is up to 25dB,the maximum of output RF power is +30dBm, and it canmaintain a good linearity. RF power amplifier needs an extra bias voltage for operation. If the RF power amplifier suspendsthe work, the offset voltage should be canceled.

In order to meet the requirements of the working status ofthe RF power amplifier chip fast switching in the systems

work. The ultra-low dropout, ultra-high-speed LDO chip isused to provide the necessary bias voltage for the RF poweramplifier in this design. The chip has an enable end EN. WhenEN is high, the chip is to provide precise, stable bias voltagefor the RF power amplifier chip. When EN is low, the chipimmediately stops working and cut off the RF power amplifierchip bias voltage, the RF power amplifier chip is in the standbymode.

HMC286 chip is used as the Low-noise amplifier, which best band is 2.3GHz-2.5GHz. It can provide gain of 19dB ForRF small-signal. Due to the bandwidth of the chip is big; Inorder to further reduce interference, the narrow band-pass-filterBF2500 with a center frequency of 2.4GHz is inserted in low

noise amplifier and antenna in the design. The received signalsof antenna can be filtered to retain only 2.4GHz band. The ratiosignal to noise can be enhanced.

The single-pole double-throw CMOS RF switch chipPE4237 is used in this design. It used to the high-speedswitching from DC to RF signal and fully meets the designrequirement.

Figure 3. RF front circuit structure 

 B.  Software Structure

The running course of the application program has beengiven in the Fig. 4.When the node’s power is turned on; theapplication program firstly initializes the OS, then, thehardware devices of the node are initialized, e.g. theenvironment monitoring sensor, the wireless communicationmodule and the ports or function modes of the MCU. Secondly,

the tasks of the node are added into the Task Control Block(TCB), and scheduled upon the priority level by the OS.

CC2530_Route_Task ：This task is the important part of

the protocol stack. Its function is dynamic routing backup.

Figure 4. μC/OS II application program

In a traditional wireless network, there is only one piece ofrouting information at a certain time. When the link is blocked,a long time is need in the process of rebuild routing. This leadsto the phenomenon of loss of data and system communicationlow reliability.

In this paper, the dynamic routing backup mechanism isadded in the Z-Stack protocol stack, terminal node to thecoordinator of the multiple routes are calculated based on thestrength of the Received Signal Strength Indication(RSSI) ofwireless sensor nodes. They are backed up in the local routingtable. The routing information is be refreshed in time. Whenan exception occurs in communication, it automaticallyswitches to the backup route to re-communicate. Themechanism has the advantages of fast response and highadaptive. In practical applications the PC software can real-time monitor the ZigBee network routing topology.

Fig. 5 shows a method for determining the network

topology for any given network using a subset of the Z-StackZDO (Zigbee Device Object) layer APIs.

Using IEEEAddrReq(), one can start the process by issuingthis request to the PAN coordinator since it always has shortaddress 0x0000. The ReqType parameter should be set to 1, toobtain the list of devices that have associated to thecoordinator.

By using the callback function IEEEAddrRspCB, one canobtain the list of associated devices which will include theirshort addresses, as well as the IEEE address of the coordinator.The NumAssocDev parameter in the callback function returnsthe number of devices that are associated with the coordinator.

Figure 5. Sequence diagram for discovering network topology 

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Once the first list from the coordinator is returned, one canrepeat the above procedure targeted at each short address in thelist. By iterating this procedure over all parents and children,the application will be able to “map out” the topology of theentire network.

III.  SYSTEM IMPLEMENTATION AND TEST

In this section the monitoring system has been tested,including the hardware and the software, in order to analysesand evaluate the whole system.

Figure 6. Output power of the wireless sensor node

Fig. 6 shows the capability of the RF Circuit. The capabilityof this circuit is the key of the long-distance communicationamong the nodes. Test parameters to select the frequency2405MHz and enable the power amplifier module and low-noise amplifier. Continuous carrier output test. From this picture, we can see that the output power of the node is+25.99dBm. In our testing course, this kind of output powercan realizes the requirement, which means that the nodes cancommunicate with each other within 1.5km.

Figure 7. User tier application program

The overview of the User tier application program has beengiven in the Fig. 7. On the left, there are six nodes in thenetwork, except the Coordinator Node. The program can gathermonitoring data, the network address and the working statusfrom these nodes. The hierarchical topology structure will begiven, if the “Topo” button is pressed. The details of thehierarchical topology will be described on the right. Thisfigure can be real-time monitoring of network status.

Fig. 8 shows the monitoring data of one node in thenetwork. The Node ID is “7559”, which means the node’s shortaddress in the network. In order to test the sensitivity of thenode, the node described has been put into a steady area, for amoment. During the testing period, a kind of specific conditionis added in the environment of the testing area for a short timeand then removed immediately. Obviously, the monitoring datacan be observed via the windows of the application program.The cycle of the monitoring data is 0.5s; and Fig. 8 also showsthe changing trend of the environment around the node.

0 100 200 300 400 500 600 700 800 900 10004

4.5

5

5.5

6

6.5

7

7.5

8

8.5

Time (s)

         P

         H

 Fig. 8 Monitoring data of one node

R EFERENCES  

[1]  Xianghui Cao, Jiming Chen, Yan Zhang, and Youxian Sun,“Development of an integrated wireless sensor network micro-environmental monitoring system,” ISA Transactions, vol. 47, pp. 247-

255, April 2007.[2]  Jiang Peng, “The Design of Wetland Water Environmental Monitoring

System using Digital Video based on Wireless Sensor Networks,” IEEEComputer Society, vol. 2, pp. 391-395, 2009.

[3]  Alessandra Flammini, Daniele Marioli, Emiliano Sisinni, and AndreaTaroni, “Environmental Telemonitoring: A Flexible GSM-DECT-BasedSolution,” IEEE Transactions on Instrumentation and Measurement, vol.56, pp. 1688-1693, October 2007.

[4]  Justin B. Ong, Zhanping You, Julian Mills-Beale, Ee Lim Tan, BrandonD. Pereles, and Keat Ghee Ong, “A Wireless, Passive Embedded Sensorfor Real-Time Monitoring of Water Content in Civil EngineeringMaterials,” IEEE Sensors Journal, vol. 8, pp. 2053-2058, December2008.

[5]  Guillermo Barrenetxea, Francois Ingelrest, Gunnar Schaefer, and MartinVetterli, “Wireless Sensor Networks for Environmental Monitoring: TheSensor Scope Experience,” Int. Zurich Seminar on Communications, vol.7, pp. 98-101, 2008.

2012 International Conference on Optoelectronics and Microelectronics (ICOM)

978-1-4673-2639-1/12/$31.00 ©2012 IEEE 492 Aug,23-25,.2012