Modular design of a novel wireless sensor node forsmart environments

Massimo Grisostomi, Lucio Ciabattoni, Mariorosario Prist, Luca Romeo, Gianluca Ippoliti, Sauro LonghiDipartimento di Ingegneria dell’Informazione, Universita Politecnica delle Marche

Via Brecce Bianche 12, 60131 Ancona, ItalyEmail: {m.grisostomi, l.ciabattoni, m.prist, l.romeo, g.ippoliti, s.longhi}@univpm.it

Abstract—Most of the existing commercial node architecturesprovide little flexibility and configurability. This limitation con-strains the usability of the same node across various applications,including the ambient intelligence issue. In this paper a novelarchitecture for the design of a modular wireless sensor nodeis proposed, dividing the connection and sensing functions intwo separate boards. The division of the wireless transducerinterface module (WTIM) in two independent boards allows toperform in a separate way the connection and sensor interfacingfunction of the WTIM always respecting IEEE 1451 standards.The versatility of the novel architecture has been tested intwo different application scenarios. In the first application themodular node has been used in a factory to monitor the efficiencyand reliability of the production line. The designed node has beenexperimentally tested and results shown. Concerning the secondapplication, a smart home approach is proposed. Using differentsensing boards, an architecture to monitor in a non-invasive wayseveral home parameters has been presented.

Index Terms—Wireless Sensors Network, Modular WirelessNode, IEEE1451 Standard, Ambient Intelligence.

I. INTRODUCTION

The topic of smart environments, also called ambient intel-ligence, is nowadays one of the hottest topics in media andresearch centers. According to [1], smart means having thecapability to autonomously collect and apply knowledge whileenvironment is made up of our surroundings. In an engineeringperspective the so called ambient intelligence can be obtainedembedding sensors and actuators in an environment to auto-matically react to users, devices and machines [2]–[4]. Therecent interest in this topic can be attributed to several factors.

1) The growing availability on the market of small andinexpensive sensors and devices easily embeddable.

2) The worldwide diffusion of networking technologies,such as Wi-Fi, Ethernet and Bluetooth that makes easierthe communication between devices.

3) The presence of small computing devices (such as smart-phones, tablets and netbooks) in almost every dwelling.

The first step to achieve the ambient intelligence is theinstallation in any environment of several devices to detect itsstate and provide information to automated control systemsor human supervisors. In many cases the adoption of standardwired solutions to supply power and acquire sensors data couldsuffer of various problems thus making harder the realizationof a sensor network (e.g. the need of expensive and oftencomplex installation and the lack of flexibility in placingsensors). In this scenario a wireless solution adopted both for

data transfer and power supply could clearly be a solutionbut, on the same time, still poses many challenges. WirelessSensors Networks (WSN) technology has been widely studiedin many universities and research centers in recent years [5]–[7]. WSN are composed by sensor nodes that autonomouslyoperate gathering sensors information and combining bothcommunication and computation capabilities in a small formfactor. These nodes, establishing a wireless link, collaboratewith each other to execute application tasks. The main ob-stacles to the spread diffusion of this technology are mainlyrepresented by communication issues (in terms of reliabilityand latency), power supply issues (nodes battery poweredneed the lowest power consumption possible) and flexibility[8], [9]. While on one hand this technology offer to usersthe dream of a high flexibility level sensor network, in thepractice there are various constraints that move the dreamfar away from reality. Most of the existing commercial nodearchitectures indeed provide little flexibility, configurabilityand the absence of interoperability between them. Daughterboards provide sensing capabilities but the processing andcommunication modules are fixed and cannot be often ex-tended. These limitations constrains the cross-usability of thesame node in different applications and the use of differentbranded nodes in the same application. Due to these problemsthe automation of a building can be extremely expensivethrough the installation of a WSN. A set of solutions for designvariation and miniaturization in each of the functional circuitblocks [10]–[12] has been proposed in literature together withsome initiatives to address the interoperability problem in thehome automation such as UPnP (Universal Plug &Play) [13] orJini [14]. In this paper we face the flexibility and customizationproblem presenting a novel architecture for the design of amodular wireless sensor node dividing the connection andsensing functions in two separate boards. The new architecture,providing a higher level of customization for the whole WSN,makes possible the implementation of different features usingthe same communication structure following the IEEE 1451standard. Two applications of the node with different plugand play sensing modules have been proposed. The consideredapplications concern cost effective solutions for the monitoringof a line production system and a smart house. The paper isorganized as follows. The proposed innovative design of thenode and introduction to the IEEE standards are discussed inSection II, the hardware chosen for the prototype is reported in

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Section III. The proposed applications are described in SectionIV where the modular node has been used in a factory tomonitor the efficiency and reliability of the production lineand, using different sensing boards, to monitor in a non-invasive way home parameters.

II. WIRELESS SENSOR NODE DESIGN

Nowadays in all the hottest markets the compatibility be-tween systems plays a crucial role for their success and for thedevelopment of every involved technologies. In this context thestandardization for wireless nodes has a great impact on WSNmarket success. The standardization helps to decrease the costof the system deployment and industrialization reducing onthe same time the cycle of development. Among the existingand emerging standards for WSN used for factory automation,IEEE 1451 has been used for the design of proposed WSN.Furthermore, the developed prototype system, named ArgosD,facilitates the flexible connection of different sensing devicesas shown in section IV.

A. IEEE 1451 Standards

IEEE 1451 is family of standards introduced to add plugand play capabilities to smart transducers. It has been devel-oped by the Institute of Electrical and Electronics Engineers(IEEE) Instrumentation and Measurement Society’s SensorTechnology Technical Committee. As transducers, used forindustrial control and process monitoring, are a crucial part ofthe WSN technology a coherent and open standard for thesesensor interfaces is the key for the market successes [15]. Theintegration, interoperability and scalability with the existingwired system are the main aims of the standard [16], [17].Different versions of the standard have been proposed since1997:

• In 1997 IEEE 1451.2 [18] specified the key definition ofdata formats and communication protocols for TransducerElectronic Data Sheet (TEDS).

• In 1999 IEEE 1451.1 [19] settled a smart transducerobject model in frame of network-capable applicationprocessors (NCAPs) to support multiple control networks.

• In 2003 IEEE 1451.3 [20] offered technical solutions forinterfacing multiple and physically separated transducersextending the point-to-point configuration to distributedmultidrop systems.

• The IEEE 1451.4 in 2004 [21] introduced the mixed-mode interface (MMI) to connect transducer modules ina plug and play mode to instruments, computers andNCAPs.

• IEEE 1451.5 [22] in 2007 defined the wireless com-munication and TEDS formats and specified sensor-to-NCAP connection for Wi-Fi, ZigBee, ultra wide bandand Bluetooth.

• The IEEE 1451.6 has been proposed as a draft to interfacethe TEDS using the high-speed CANopen network [23].

• The last member of the family, the IEEE 1451.7 wasintroduced in 2010 [24] to facilitate the communicationbetween smart RFID systems and integral transducers.

Fig. 1: New network architecture and IEEE 1451 standarddivision.

Fig. 2: Connection board architecture.

B. Modularity

As defined in IEEE standard 1451.5 [22] a wireless trans-ducer interface module (WTIM) is a device connected totransducers and, via Dot5AR protocol, to the NCAPs. AWTIM differs from the standard TIM, as defined in IEEEStd 1451.0 − 2007, only for the wireless communication tothe NCAP and provides two different functions. On one sideit allows the connection with the NCAP node while on theother makes possible the sensors interfacing. The main designnovelty presented in this paper is the division of the WTIMin two independent boards to perform in a separate waythe connection and sensor interfacing function of the WTIMalways respecting IEEE 1451 standards, as shown in Fig. 1.

The connection board (represented in Fig. 2) performs onlyactions involved in the wireless connection process with theNCAP node: it maintains in memory only the wireless relatedPHY TEDS and communication module commands. For whatregards transducers related commands it acts as a gateway forthe sensor board.

The sensor board (a sample of a comfort sensing board isrepresented in Fig. 3) has another micro controller to per-form the remaining functions: transducers interfacing, signalacquisition and conditioning. In this board TEDS are storedand all the information coming from the network (through thecommunication board) processed.

Fig. 3: Comfort sensor board architecture.

Fig. 4: Sensor board (on the left) and connection node (on theright) real dimensions compared with a 2 ecoin.

Since the IEEE 1451 standards do not provide a specifichardware communication protocol between the two boards, ithas been adopted a UART protocol with a 3.3 V line.

III. WSN HARDWARE

1) Core Micro MSP430F1611: The core micro chosen forthe sensor node is the ultra low power micro controller of theTexas Instruments MSP430 family [25]. The architecture iscombined with five low power modes and optimized to achieveextended battery life in portable measurement applications.

2) Core Radio CC 2520: The CC2520 is a ZigBee (IEEE802.15.4) transceiver for the 2.4 GHz unlicensed band. Thischip enables industrial grade applications by offering severalfeatures as reported in table I.

IV. MODULAR NODE APPLICATION

The present part of the work aims to provide practicalsolutions to the ambient intelligence problem using differentsensor boards connected to the proposed modular node. Theconsidered environments have been divided into two maincategories: industrial and domestic ones. For what concernsthe industrial scenario the results of a real WSN installedin a factory will be reported, while in the domestic one acost effective WSN architecture will be proposed for energy

TABLE I: Radio transmitter CC2520 key features.

Data Type Value

Adjacent channel rejection 49 dB

Alternate channel rejection 54 dB

Temperature range -40 to +125◦C

Supply range 1.8 V - 3.8 V

RX (receiving frame, -50 dBm) consumption 18.5 mA

TX (@ 0 dBm) consumption 28.5 mA

Power Down consumption < 1 µA

Fig. 5: WSN and communication architecture designed for theline production monitoring .

and comfort monitoring. In both proposed scenarios, modularnodes (shown in Figure 4) and a custom programmer are usedto create Low Power Area Networks (LowPans), as describedin [22], adopting a Contiki operative system. In these project2 main hardware categories are considered:

1) wireless sensor nodes: acquire analog and digital inputs(depending on the application) and send measured valuesto the edge router every second using the 6LowPanstandard

2) wireless edge router: opens the virtual channel to senddata from WSN to the server, provide the communica-tion between LowPans and Internet, implementing allthe required features

A. Industrial Ambient Intelligence Application

The focus of the first part of the section is the integrationof wireless sensor network (WSN) technologies in industrialapplications as described in [26]. In particular we considered apacking factory for the analysis and experimental tests, whereraw materials and semi-finished products (SF) are refinedthrough sequential operations to produce the final product (apackaging box). The sensing board for the node was composedby two types of digital sensors. The first one is the rollerlimit switch, a contact sensor with two boolean states used tomonitor the setup time of each section of the line production.The other sensor is a photoelectric one with an infrared lighttransmitter and a photoelectric receiver, mainly used as anitems counter. The developed architecture, shown in Fig. 5 istested in a typical industrial scenario, where WSNs have to beconfigured to provide remote monitoring service for the lineproduction status.

We analyzed the overall equipment effectiveness (OEE) andthe total effective equipment productivity (TEEP) of the cell,

TABLE II: June-July 2013. Effectiveness indexes computedfor the four different product lines.

Data Type Line A Line B Line C Line D

TEEP 74, 2% 43, 1% 69, 9% 65, 1%

OEE 69, 0% 28, 3% 65, 7% 58, 4%

TABLE III: June-July 2013. Reliability indexes computed forthe single machines of the manufacturing cell.

Machines MTTR (min) MTBF (min)

Loader 15.3 436.0

Printer 8.6 541.3

Die Cutter 8.6 501.0

Sticker 9.3 287.1

Bender 9.4 313.9

Labeler 6.9 162.4

Unloader 6.3 53.2

as defined in [27]–[29]. These indexes represent a measureof the value added to production through equipment, whichis a function of machine availability, performance efficiencyand the rate of quality. Results of this application have beenreported in [26], where historical and real time performanceindexes have been computed. Tables II and III show a sampleof the efficiency and reliability indexes computed for differentproduct lines and machines.

In particular the analysis results showed a dramatic loss ofefficiency for the higher customization level products (LineB).

B. Smart House Architecture

Lot of research focuses on non-invasive wireless sensorsused in existing home environment to transform it into a smarthome. In this work we propose an application of the presentedmodular wireless sensor node to create a smart environment.By placing sensor nodes everywhere in the house, the tem-perature, brightness, noise level, humidity as well as powerabsorbed by appliances can be collected and analyzed. Twomain sensor boards for our modular node ArgosD have beendesigned and realized to be integrated in a house, as Fig. 6shows.

1) Comfort Sensing Board: The predicted mean vote, oneof the most important indexes for the estimation of the indoorcomfort [30], [31], is determined by several parameters. Inthe design of our comfort board, as shown in Figs. 3 and 4,we had to consider all the parameters necessary for the PMVcomputation: the indoor air temperature, air humidity, air flowrate, noise and brightness. The sensors we used are:

• Humidity and Temperature Sensor model HIH6130: themain features of this sensor are temperature compen-sation, a digital I2C or SPI output, energy efficiency(required for a WSN application) and, obviously, smallpackage. The voltage supply can operate down to 2.3Vdc, allowing its use without compromising battery life.

Fig. 6: Nodes placement in a typical house.

TABLE IV: Temperature/Humidity sensor HIH6130 features.

Characteristic Humidity Temperature

Resolution 0.04 % 0.025◦C

Accuracy 4 % 1◦C

Response Time 6 - 8 s 5 - 30 s

Operating Range 0 - 100 % −25 - 85◦C

Another built in feature of the sensor is its capability togo into the so called deep sleep mode when not takinga measurement within the application, consuming only1 µA of power versus 650 µA in full operation. Thesleep mode helps to maximize battery life thus reducingis power supply size and the application’s overall con-sumptions.

• Acceleration sensor model MMA7455L: a digital out-put (I2C and SPI) capacitive accelerometer. The mainfeatures are: built in signal conditioning with a low passfilter, temperature compensation, self-test, capability todetect 0g. The power consumption, one of the mostimportant features of the sensor, is 400 µA during theoperation mode and 10 µA in standby mode.

• Brightness sensor BH1751FV I: a digital ambient lightsensor for I2C bus interface with a supply current of 120µA and a standby current of 0.85 µA

• Noise sensor CMC − 5042PF − AC: is an omnidirec-tional noise sensor with a sensitivity of −42 dB.

2) Energy Sensing Board: The active power absorbed bysome appliances and the overall household consumption canbe measured with a microchip MCP3905A, providing threemeasures:

• the instant active power measured with a frequency of20− 80 Hz

• the energy counter with a frequency < 1 Hz• the voltage - current phase

V. CONCLUSION

This paper presents novel modular design of a wirelesssensor node. The node, following IEEE 1451 standard, iscomposed by two main boards, related to the connection and

the sensor interface respectively. The main purpose of thisdesign is to standardize the communication for the entiresensor network giving on the same time the chance to usea wide variety of sensors. This sensing system has a varietyof important applications, including energy monitoring, homeautomation, industrial plant monitoring. Two different appli-cation scenario of the node have been presented. In the firstapplication the modular node has been used in a factory tomonitor the efficiency and reliability of the production line.The WSN designed has been experimentally tested and resultsshown. Concerning the second application, we propose a smarthome approach using the versatility of the node architecture.Designing an energy and a comfort sensing boards, an solutionto monitor in a non-invasive way several home parameters hasbeen presented.

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