A Zigbee based wireless sensor network for sewerage monitoring

Conference Paper (PDF Available) · January 2010with 5,564 Reads
DOI: 10.1109/APMC.2009.5384245 · Source: IEEE Xplore
Conference: Microwave Conference, 2009. APMC 2009. Asia Pacific
Abstract
Blockages in sewers are major causes of both sewer flooding and pollution. Water companies which fail to tackle this problem face hefty fines and high operational costs if they unsuccessful to provide a practical solution to prevent flooding. As a result, the detection of sewer condition is routinely required to inform on the best course of action to eliminate this critical problem. This paper presents a novel low cost wireless sensor technology to detect blockages proactively, and feed these event data back to a central control room. The practical deployment of the proposed WSN in an urban area will be demonstrated. In addition, the challenges of this technology in a field trial and the recorded data in terms of the sensor and communication reliability will be addressed.
A Zigbee Based Wireless Sensor Network for Sewerage Monitoring
C.H. See#1, K.V. Horoshenkov#1, S.J. Tait#1, R.A. Abd-Alhameed#1, Y.F. Hu#1, E.A.Elkhazmi#2 and J.G.Gardiner#1
#School of Engineering, Design and Technology
University of Bradford
Richmond Road,
Bradford, West Yorkshire, UK, BD7 1DP
1c.h.see2@bradford.ac.uk
#The Higher Institute Of Electronics, Bani Walid-Libya
2eaelkhazmi@hotmail.com
Abstract — Blockages in sewers are major causes of both sewer
flooding and pollution. Water companies which fail to tackle this
problem face hefty fines and high operational costs if they
unsuccessful to provide a practical solution to prevent flooding.
As a result, the detection of sewer condition is routinely required
to inform on the best course of action to eliminate this critical
problem. This paper presents a novel low cost wireless sensor
technology to detect blockages proactively, and feed these event
data back to a central control room. The practical deployment
of the proposed WSN in an urban area will be demonstrated. In
addition, the challenges of this technology in a field trial and the
recorded data in terms of the sensor and communication
reliability will be addressed.
Index Terms — WSN, Wireless sensor
I. INTRODUCTION
Sewer flooding (DG5 Other Causes) and pollution
incidents are significant issues in the wastewater business
process in the water industry. One of the most pressing issues
for prevention of sewer flooding and pollution is sewer and
gully blockages [1]. Monitoring and maintenance are
important part of the many water companies business to
prevent catastrophic failures that can shut down a facility
which may cost several millions pounds per day. On top of
that, water industries regulated by several UK’s government
agencies, such as the OFWAT and EA, may be required to
pay hefty fines for not meeting the basic standard
performance of their services. Currently, many water
companies have deployed telemetry systems to replace some
of the manual operations, running costs remain expensive.
Low cost wireless sensors may be the only cost-efficient
option to replace traditional visual inspection which is
extremely inefficient and costly. Moreover, existing telemetry
systems require extensive cabling for (Public Switch
Telephone Network) PSTN and power and cannot be
deployed over a large catchment area because of the cost.
Low cost and low power sensors could be deployed over an
extensive footprint network and provide early warning of
impending failure offering time for maintenance teams to
prevent service or regulatory compliance failure.
This paper describes a practical implementation of a
low cost wireless WSN using Zigbee communication and
acoustic sensor technologies to monitor the water level of the
gullies in a residential urban area. The purpose of this field
trial was to evaluate the preliminary design of the proposed
system in terms of durability of sensors, sensor nodes and
gateways and reliability of communication under real
operational conditions and within a typical urban
environment.
Fig.1: Wireless Sensor Network- System Architecture
II. SYSTEM ARCHITECTURE
In this section, the architecture of the proposed low power
mesh network wireless sensor system will be discussed.
Inherent power limitations of radio communication devices
might introduce hard restrictions on the coverage of the WSN
[2]. Due to this limitation, direct communication between
sensor and base station is not always possible especially over
a difficult radio environment with strong attenuation. In order
to overcome this difficulty and to extend the communication
distance, an obvious way forward is to use multi-distributed
nodes that use multi-hops to send the data over these nodes
978-1-4244-2802-1/09/$25.00 ©2009 IEEE
731
Fig.3: Wireless Sensors Distribution on field trial
(sensors) on the way to the base station. As can be illustrated
in Fig.1, by implementing a mesh network communication
configuration, this WSN allows for continuous connections
and reconfigurations around blocked paths. This might
results in hopping from sensor node to node until a
connection can be established with the base station [3-5]. It
should be noted that the mesh networks posses the self-
healing capability that will operate even when a node breaks
down or a connection fails. As a result, it forms a very
reliable network. Once the data is received by the data
gatherer/hub, it will be stored and published on a webpage
via connection to the internet. By accessing the internet,
remote mobile devices can request the recorded data with the
right user name and password.
A Zigbee based short range WSN was selected for this
application due to its attractive features such as low data rate,
low power consumption, simple communication
infrastructure, low latency and capability to support one
master and up to 65000 slave control units. In general, the
proposed system has led to the development of knowledge
and expertise in four areas of research: a) Embedded Antenna
design; b) Sensors and Instrumentation for use in water
industry assets; c) Wireless communications and distributed
wireless sensor networking; d) Remote monitoring of water
related assets.
A. Crossbow Mica2 Sensor Node
The Crossbow Mica2 [6] node is an advanced tiny wireless
platform for smart sensors, which is constituted by CC1000
radio, Atmega 128L processor, 128kB Flash, 4kB RAM and
10 bits ADC. By enabling the Low Power Listening (LPL)
mode of this platform, it will perform the operation in the
lowest duty cycle mode. Hence, this wireless module can
prolong the battery life significantly. An important part of
this system is the water level sensor element. There are a
number of water level sensors available in the market.
However, many commercial low cost water level sensors are
unreliable and too delicate to be used in the hostile gully
environment. In order to reliably and effectively measure the
water level of a gully, a novel and low cost acoustic sensor
was designed and developed.
There are two ways of using a sonic transmission to
detect the water level, i.e. (i) By measuring the time of flight
from transmitter to receiver – it will be faster in water, (ii) By
using the level of the received signal – the received signal
will be louder if the transmitter and receiver are both under
water. Both of these methods of detection will require a
driver for the acoustic transmitter and an amplifier for the
received signal. Method (i) suffers from the leaves or debris
and most likely to cause a false alarm. Therefore, method (ii)
was adopted in this project. A novel acoustic probe [7] and
data acquisition circuit (DAC) board were developed to
identify three status of water level, i.e., Low, Normal and
High. The DAC board was designed to operate in low power
consumption mode and considerably extend the life time of
the sensor.
Fig.2: Deployment of wireless sensors in gullies and data gatherer
on lamppost.
B. Antenna design
Unforeseen RF transmission disruption can occur when
deployment of wireless sensors is implemented over a large
area. Multipath reflections occur when an RF signal takes
different paths on the propagation channel between the source
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nodes (e.g., a radio NIC) to a destination node (e.g., access
point). In this scenario the received signal can be routed
along different paths, which causes the signal to bounce in
different directions. As a result, some of the radio signals
arrive with a delay as they travel longer paths to the receiver.
This is likely to corrupt the information contained in the
broadcast message and cause significant delay to the whole
communication system. To alleviate this problem in mesh
radio network, hop-by-hop algorithm can be adopted.
Conventional low power mesh network of wireless
communications sensors suffers from limited communication
range. In order to achieve an optimum reasonable
communication distance with minimum power consumption,
the antenna plays an important role in implementation of the
wireless sensor network (WSN).
The objective of this project is to design, develop and
implement a gully pots wireless monitoring system.
Therefore, the proposed wireless sensors have to be able to
operate in a harsh environment, with high radio signal
attenuation (lossy and watery) surroundings and invisible to
third party. As a result, the commercial off the shelf (COTS)
type aerial which is a monopole, is not suitable for this
application. This requires redesigning an aerial to satisfy the
demands of the proposed WSN. Ideally, the proposed antenna
has to provide the following characteristics: (1) able to
operate from 902MHz to 926 MHz frequency band, (2) have
omni- directional radiation patterns, (3) high gain, (4)
robustness, (5) low cost and profile and (6) ease of
installation and maintenance. For the proposed system, an
embedded microstrip antenna was designed, tested and
implemented within a waterproof enclosure. It is believed to
have a high potential and feasibility to be adopted in
underground infrastructure monitoring. The description of
this antenna is provided in [8].
C. Stargate Platform
Stargate platform is a linux operating system based on a
mini-computer [9-10]. In this present application, it is acted
as a data gatherer/hub which collects the data from all the
wireless sensors. As can be seen in Fig. 2, it was mounted on
a lamppost for optimum coverage of the monitored area.
Stargate is programmed to operate into sleep mode when it is
idle to conserve the battery power. In addition, GPRS was
used to transfer the received data from Stargate to the remote
server. Constantly turning on the GPRS connection will
flatten the battery within days so in order to maintain the
battery life for months; Stargate sends the recorded data back
to the remote server once a day based on GPRS connection.
III. FIELD TRIALS
A dense residential area in Bradford, UK, was chosen to carry
out the field trial. There were two main reasons for the selection of
this site: (i) In this area, every single house only has one gully
which collected all the wastewater, such as hot water, cold
water, bath water full of hair, rain water, kitchen sink water
full of fat. ie a high risk wastewater disposal system, and (ii)
the topology of the site allowed the proposed Zigbee mesh
network wireless sensor system to be tested easily. The site
was a row of residential houses, sensors could relay
information between its neighbour to reach the data gatherer.
Fig.3 shows the distribution of the Zigbee-based
communication system which currently includes eight gully
monitoring units and a stargate. As can be observed, the
shortest and longest distances between the sensor to sensor
(STS) and sensor to hub(STH) are 5.5m and 38.5m, and
12.3m and 66.5m respectively. As can be noticed, the red
triangle spot and the white ring symbols in Fig.3, indicate the
location of the data gatherer and sensors respectively.
For the purpose of extending the battery life of the
Zigbee flooding monitor up to a long as possible (ideally two
years), the proposed Zigbee monitor was programmed to
operate in the following modes:
1. A two way low power mesh network communication
was designed and implemented into the proposed
wireless system. In order to keep the minimal power
consumption in the sensor nodes, a low power listening
(LPL) mode was enable on the radio module (CC1000)
of the Crossbow transceiver. The LPL mode enabled the
radio module to go into sleep i.e. extreme LPL mode,
instead of turn off the radio completely. By implementing
this mode, the sensor and base station were in a 1% duty
cycle, maximum 0.89 packet transmission/reception per
second and 0.258kbps effective throughput operation
mode [11].
2.The sensor was programmed to wake up from sleep mode
to measure the data in every five minutes. If it detected
five consecutive flooding/leaking alarms, then it
transmitted the radio packet to either nearby sensor node
or directly to data gatherer/hub depend on the detected
receive signal strength indication (RSSI) level, otherwise,
it operated in sleep mode to keep the current
consumption to a few microamperes. In general, there
were three operation modes in this application, which
were sleep mode, sensing mode and radio broadcast
mode, these modes were corresponding to average 20uA,
9mA and 18mA current consumption, respectively.
3.Once it detected a low/high alarm, it sensed the RSSI,
from the hub as well as its neighbour sensor’s node. Then,
it compared the RSSI and find out the best route to relay
the data back to the GPRS server. It should be noted that
the open source Xmesh reliable route protocol [12] was
employed for this application. However, for the health
check purpose, the sensor broadcasted a health condition
packet back to the hub to indicate its battery level and
water level condition on a daily basis.
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IV. RESULTS AND DISCUSSION
From the field trial, according the daily data received from
the server, it was observed that the reliability of the proposed
Zigbee system can reach up to 80%. Fig.4 interprets the
reliability of the proposed wireless communication system
over each stage of the field trial. In general, this field trial has
been divided into four stages. In the first stage, eight sensors
and one data gatherer (i.e. stargate) were installed. It should
be noted that after the installation there are 2 sensors (ID
4520 and 4521) working reliably which operate under LOS
condition.
V. CONCLUSIONS AND RECOMMENDATIONS
This paper presents a practical implementation of the Zigbee
based wireless communication system on an urban residential
area. These proposed technologies will enable to transfer
effectively and process data from large numbers of
potentially diverse sensors distributed within a sewer
infrastructure network to achieve potentially zero pollution
and DG5 other causes. Outcomes from the field trial enabled
researcher in this research area to gain expertise in the issues
associated with the practical monitoring of the performance
of elements of the urban sewerage infrastructure managed in
the UK water industry.
By adding relay points (i.e. repeaters) which was about 40m
to 70m away from the hub and changing the orientation of the
aerial of the hub, in addition of installation a high gain aerial
of the hub, which is corresponding to stage 2,3 and 4 in Fig.4,
the efficiency of the proposed system can be improved
considerably. As a result, 5 out the 8 of the sensors were
working reliably over trial period. However, this
communication reliability can be improved in future and
applied to large scale deployment by increasing the frequency
of the transmission of the Zigbee sensor, installing additional
low cost relay points and improve the aerial design on the
hub. This can be done by introducing multiple aerials on the
hub to mitigate the fading effects of a multipath environment.
Moreover, adding amplifier on the reception side of the
Zigbee radio module will improve the receive sensitivity of
the hub. As for the sensors that did not work with a high
reliability, this was due to unforeseen man-made issues, such
as covering the sensors with rubbish and concrete blocks.
These activities impaired the radio communication
significantly and invalidated the communication reliability of
the proposed system. An investigation has been carried out to
pinpoint the reasons on what possibly blocked the radio
communication on those gully monitoring units (ID: 4510,
4512 and 4513). According to findings from the investigation,
it seemed that failure of Sensors ID 4510, 4512 and 4513 can
be attributed to covering the gully.
ACKNOWLEDGMENT
The authors acknowledge the support provided by funding
from Yorkshire Water Services and the Technology Strategy
Board, via the KTP Project “The development of a new
sewerage telemetry system”
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Fig.4: Communication Reliability of the proposed system
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  • ... Power system applications Chen and Lee (2011) , Kantarci and Mouftah (2011), Lim et al. (2010), Lin et al. (2010), Yang et al. (2007, Gungor and Hancke (2010), Wang (2009), Cao et al. (2008), Magno et al. (2015, Ahmad et al. (2015), Jiang et al. (2015), Viani et al. (2014) Roadside and transportation applications Ceriotti et al. (2011), Bruno et al. (2015), Ferreira et al. (2010), Festag et al. (2008), Rahim et al. (2010), Losilla et al. (2011 Jeong et al. (2008), Tseng et al. (2007), Przybyla et al. (2010), Diamond et al. (2008), Arora et al. (2005), Barbeau et al. (2008 Healthcare applications Villacorta et al. (2011), Morreale (2007), Ko et al. (2009, Chung and Liu (2013), Yilmaz et al. (2010), Ghasemzadeh et al. (2008 Gas monitoring Lim et al. (2011), Jeong et al. (2008, Ni and Chin (2009), Jawhar et al. (2008), Yoon et al. (2011), Wan et al. (2011 Gully pot monitoring See et al. (2012), Gomez and Paradells (2010), See et al. (2009), Cao (2009), Lin et al. (2008, Lea and Blackstock (2014) Air pollution monitoring Mao et al. (2012), Jung et al. (2011), Bagula et al. (2012), Felstead et al. (2007 Structural monitoring Zarzo et al. (2011), Zeng et al. (2011), Capella et al. (2011), Nagayama et al. (2006), Garcia-Diego et al. (2010), Kim et al. (2007), Ceriotti et al. (2009), Xu et al. (2004 Urban temperature monitoring Thepvilojanapong et al. (2010), Croft et al. (2010 Solid waste monitoring Catania and Ventura (2014), Longhi et al. (2012), Boustani et al. (2011 Precipitation monitoring Li et al. (2010), Murty et al. (2008 Water pipeline monitoring Jin and Eydgahi (2008), Stoianov et al. (2007), Whittle et al. (2013), Almazyad et al. (2014 Ubiquitous geo-sensing Resch et al. (2010), Resch et al. (2009 Commercial asset tracking Mason et al. (2007), Liu et al. (2007), Wheeler (2007), McKelvin et al. (2005 Urban Internet Riva (2007), Whitehouse et al. (2004), Keh et al. (2014), Kruger et al. (2015, Jalali et al. (2015), Chang et al. (2010), Honjo et al. (2015 2. Power system applications ...
    ... While some sensor nodes are fully functional for all time; these are called coordinator nodes as they act as a bridge between data collector and other partially active nodes. In See et al. (2009), the authors have documented field trials in urban area of Bradford (UK). The wireless sensor network based on mesh topology and governed by Zigbee communication was deployed with acoustic sensors for monitoring any leakage or blockage in the sewage system. ...
  • ... For example, if a waste water site was receiving an influx of influent during an antisocial period, on a site that is not 24hr manned, there could be a process risk that leads to an environmental consent breach. These breaches cost water companies large amounts in fines each year[6]. The Thames Water annual report and financial statement for 2014/15 provided pollution information, which suggested it was still exceeding the upper control limit set by The Water Services Regulatory Authority (OFWAT) [7]. ...
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  • US water utilities are faced with mounting operational and maintenance costs as a result of aging pipeline infrastructures. Leaks and ruptures in water supply pipelines and blockages and overflow events in sewer collectors cost millions of dollars a year, and monitoring and repairing this underground infrastructure presents a severe challenge. In this paper, we discuss how wireless sensor networks (WSNs) can increase the spatial and temporal resolution of operational data from pipeline infrastructures and thus address the challenge of near real-time monitoring and eventually control. We focus on the use of WSNs for monitoring large diameter bulk-water transmission pipelines. We outline a system, PipeNet, we have been developing for collecting hydraulic and acoustic/vibration data at high sampling rates as well as algorithms for analyzing this data to detect and locate leaks. Challenges include sampling at high data rates, maintaining aggressive duty cycles, and ensuring tightly time- synchronized data collection, all under a strict power budget. We have carried out an extensive field trial with Boston Water and Sewer Commission in order to evaluate some of the critical components of PipeNet. Along with the results of this preliminary trial, we describe the results of extensive laboratory experiments which are used to evaluate our analysis and data processing solutions. Our prototype deployment has led to the development of a reusable, field-reprogrammable software infrastructure for distributed high-rate signal processing in wireless sensor networks, which we also describe.
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    The author discusses the question of whether the ZigBee wireless standard, promoted by an alliance of 25 firms, a big threat to Bluetooth? ZigBee, developed for the 2.4 GHz band, looks rather like Bluetooth but is simpler, has a lower data rate and spends most of its time snoozing. This characteristic means that a node on a ZigBee network should be able to run for six months to two years on just two AA batteries, claim its backers. However, there are questions about ZigBee's viability. The target of building automation as the main application makes technical sense but it is a field notoriously slow at adopting new technologies. In other proposed applications, ZigBee seems to tread on Bluetooth's toes but the technical and price advantages are marginal and unsubstantiated: there are no finished ZigBee chips and low prices necessitate very high volumes.
  • Mica2 wireless module
    • Crossbow
    • Inc
    Crossbow, Inc., Mica2 wireless module, http://www.xbow.com/Products/productdetails.aspx?sid=174