RFID+ for Tracking Earthmoving Operations

Transcription

1 1011 RFID+ for Tracking Earthmoving Operations Ali MONTASER 1 and Osama MOSELHI 2 1 Department of Building, Civil & Environmental Engineering, Concordia University, 1455 De Maisonneuve Blvd. W., Montreal, Quebec, Canada H3G1M8, [email protected], Phone: (514) Ext Department of Building, Civil & Environmental Engineering, Concordia University, 1455 De Maisonneuve Blvd. W., Montreal, Quebec, Canada H3G1M8, [email protected], Phone: (514) Ext 3190 ABSTRACT This paper presents an automated methodology for tracking earthmoving operations in near real time utilizing RFID technology to capture data during construction. It is based on attaching low cost passive RFID tags to hauling units (trucks) and attaching fixed RFID readers to designated gates of projects dump areas. The RFID readers will identify and record the time each truck enters or exits one of these gates. The captured data will then be transferred wirelessly from the RFID reader to a computer housed in one of the temporary offices onsite and to the main server in contractor s head office. The collected data will be analyzed and processed automatically, without human intervention, to calculate the productivity of the hauling unit and report it directly to onsite personnel. Database application is developed to implement and automate the developed methodology in Microsoft Access. The developed database is used to process the data captured by the RFIDbased system to calculate earthmoving productivity in near-real-time. It can also be used in estimating productivity of similar works during planning stage. The developed methodology is expected to facilitate early detection of discrepancies between actual and planned performances and supports project managers in taking timely corrective measures. INTRODUCTION Estimating actual productivity is essential element in estimating the time and cost required to complete construction operations (Oglesby et al 1989). Manual methods for data collection, storage, retrieval and analysis are time consuming and prone to human error and may result in delayed corrective actions with undesirable cost consequences (Liu, 1995 and Sacks et al, 2002). Data collected manually usually stored on paper; rendering it difficult to access and examine. Therefore, some information items end up being not readily available to project teams to make timely

2 1012 decisions. Failure in effectively tracking construction progress and in retrieving the related information on demand may result in schedule delays and cost overruns (De la Garza and Howitt, 1998 and Ergen and Akinci, 2007). Earthmoving operations have received considerable attention from researchers and industry professional. Wide ranges of methods were used in planning of these operations in search for optimum fleet configurations (Alkass and Harris, 1988, Hajjar and AbouRizk 1999, Marzouk and Moselhi, 2004, and Moselhi and Alshibani 2009). Auto-ID and data capturing technologies allow identification, data collection, and information storage for assets without need for human intervention (Rasdorf and Herbert, 1990, McCullouch and Lueprasert, 1994, and Marsh and Finch, 1998). With its lower cost and increased capabilities, radio frequency identification (RFID) gained industry acceptance in different applications such as airport operations (Al-Ali et al, 2007), health care (Fisher and Monahan, 2008), and in transportation and highway operation (Wen, 2010). RFID technology overcomes most limitations of other tracking technologies such as bar code and magnetic strips. It does not require direct line-of-sight, not sensitive to direct sunlight, tags could not be damaged easily and can be encapsulated, if needed. It could collect data in dirty, harsh, hazardous conditions. RFID has proved to be reliable in terms of long-term data storage in harsh environments (Jaselskis and El-Misalami, 2000 and Akinci et al, 2002). BACKGROUND AND RELATED WORK RFID is a wireless communication of data through radio waves. RFID system has two main components; reader and tags. These tags contain transponders that release messages readable by specialized RFID readers. Readers could be fixed or mobile, integrated with handhelds, pocket-pcs, or standalone reading devices. Typically, the reader receives signals emitted from tags attached to objects. RFID tags fall into two broad categories, active and passive, depending on their source of electrical power supply. Active RFID tags have their own power source; usually an attached battery. The power to passive tags is provided through the reader from the tag antenna when the tag is in the read range zone of the reader. Passive tags are lowcost; they can cost as little as five cents each, and new technologies are constantly making them less costly to integrate into different materials and products (Jaselskis et al, 1995, Weinstein, 2005 and Finkenzeller, 2010). RFID technology offers significant advantages over manual documentation and traditional tracking of objects on construction jobsites. Several studies proposed the utilization of RFID technology in construction for resource tracking, progress reporting, maintenance and tracking and locating material on construction sites. (Goodrum et al, 2006, Ergen et al, 2007, Grau and Caldas, 2009, Razavi, and Haas, 2010, Lu et al, 2011 and Razavi and Moselhi, 2011). RFID gates are typically used at dedicated locations to recognize arrival dates of materials onsite. The major task of a recognition point is to report the identification of items to the system for additional processing (Goller and Brandner, 2011). Song et al (2006) developed a gate system using fixed RFID readers to identify fabricated

3 1013 pipe spools and collect other information about these spools, such as purchase order number, entry date to storage yard. Lee et al (2008) developed RFID gate sensor system, which uses the passive-type RFID tags and wireless sensor network technology based on Zigbee to build an intelligent logistics management system for construction sites. However, the developed models of RFID gate systems lack the capability of fusion of data collected from more than one sensor, which is crucial to the proposed method, as described in the following section. It should be noted that the current applications of RFID technology is limited to identification. In addition, that the developments made in this paper makes full utilization of the collected RFID data to perform near-real-time estimates of earthmoving operations. PROPOSED METHOD This paper presents an automated method for tracking and estimating productivity of earthmoving operations in near-real-time utilizing RFID technology to capture data during construction. The main RFID hardware components used in the developed method are RFID fixed reader, RFID encapsulated tags, RFID label tags and RFID labels tag printer (see Figure 1). RFID hardware could collect data in dirty, harsh, hazardous conditions. For example, the encapsulated passive RFID tag in Figure 1-a could work in temperatures ranging from -40 o C to 66 o C, with read range equal to three meters and could be attached using screws, rivets, double-sided adhesive strips or a variety of other methods. Regarding its memory size it has a capacity of 512-bit-on-chip. Also, fixed readers (Figure 1-d) could work under similar harsh conditions such as could work in temperatures ranging from -25 o C to 55 o C and protected from dirt, dust, oil, other non-corrosive material and splashing water. Readers connectivity could be Ethernet or Wi-Fi and can host applications written in Java, JavaScript, VB.Net or C#.Net (Intermec, 2011). For passive RFID label tags (Figure 1-b) and its printer (Figure 1-c), while not relatively rugged, can be used inside the truck itself knowing that it cost 5 cents per tag. Figure 2 provides an overview of the proposed method. The idea behind the proposed method is to track hauling units using low cost passive RFID tags. Soft tags can either be mounted directly on the windshield glass at the front of trucks or rugged encapsulated tag be mounted on the driver s door of trucks. The developed method uses fixed RFID readers for the gate system, at loading and dumping areas, to collect RFID singles form entering and departing trucks into and from the two areas. Once and empty truck enters the loading area, the fixed RFID reader (RFID Reader 1, as shown in Figure 2) will start receiving signals from the RFID tag attached to the truck attached and will continue receiving those signals as long as the RFID tag (i.e. the truck) remains within the reading range. This process is repeated in a similar manner, but using Reader 2, at the dumping area. In between, i.e. over the hauling and return roads, no signal is received.

4 1014 a)rfid encapsulated tag b)rfid label tag c)rfid tag printer d)rfid fixed reader Figure 1: RFID system hardware components Figure 3 illustrates the main five events that describe the entire earthmoving process, upon performing the data fusion of the two readers. These five events depict a complete cycle in the operation being modeled. Each of these events is described below. Event 1 represents, approximately, the commencement of the loading process. The approximation here has to do with limiting signal range of the passive tag used in the developed method. It is worth noting that this type of tag the maximum range of signals is three meters. As long as the hauling truck in this range, the reader will keep receiving signals from the truck. When the truck leave the loading area after finishing loading the excavated material, RFID reader 1 will register Event 2. In the proposed method, it is assumed that the truck is loaded with its full capacity; according to truck manufacturer data and soil type. This assumption is reasonable and is commonly used when the Global Positioning Systems (GPS) is employed instead of RFID. Event 3 is registered from RFID Reader 2 when the hauling truck approaches the dumping area, which also confirms the end of the hauling activity. Upon dumping the excavated material, the ruck will exit dumping area and RFID Reader 2 will register the commencement of Event 4. A cycle will be completed upon return of the truck to the loading area (i.e. commencement of Event 5). Therefore, cycle time calculations can then be performed as follows: Loading Time = Registered time of Event 2 - Registered time of Event 1 Travel Time = Registered time of Event 3 - Registered time of Event 2 Dumping Time = Registered time of Event 4 - Registered time of Event 3 Returning Time = Registered time of Event 5 - Registered time of Event 4

5 1015 Automated Site Data Acquisition Dumping Data Transfer Time Wireless Communication Dump Area Gate 1 Fixed RFID Reader 2 (Dumping area gate) 2 Travel Loaded Truck Empty Truck Return RFID Reader 2 Fixed RFID Reader 1 (Project gate) RFID Tag Radio Frequency Waves RFID Reader 1 Loading Company Data Analysis A RFID Reader Generated File B C D E Central Server Company Database Cost & Time EV Analysis & Corrective Actions Productivity Generated Reports Figure 2: Overview of the proposed method

6 1016 The data collected from both RFID Readers 1 and 2 will transferred using wireless communications to the computer onsite and subsequently transferred to central database server in the head office of the contractor. Figure 3: Diagrammatic sketch for RFID reader 1& 2 integration RFID reader will generate text file with five fields: a) RFID tag ID, which was read, b) the number of times this tag was read, c) received signal strength, d) date, e) time. By fusing the data from both RFID Readers 1 and 2 for single truck as shown in Figure 3, the activities durations within a complete cycle can be clearly defined (i.e., loading time, travel time, dumping time and return time). This process of data capturing, data fusion and processing is repeated for a number of cycles as shown in Table 1. Table 1: Events recognition and cycle time classification Date Time Tag RFID Time Cycle Cycle Event Type ID Reader (min) No. Time :12:06 BF BF BF BF BF :15:11 BF 1 2 0:03:05 Loading Time :40:27 BF 2 3 0:25:16 Travel Time BF BF BF BF :42:38 BF 2 4 0:02:11 Dumping Time :03:43 BF 1 5 0:21:05 Return Time 1 0:51:37

7 1017 To facilitate data storage, fusion and processing a relational database was developed. The database has 11 entities; interconnected with one-to-many, many-to-one and many-to-many relationships. Due to space limitation, the Entity Relationship (ER) diagram is not included. The model was created to work on enterprise level; to facilitate tracking of hauling units not only at the project level but also of the contractor entire fleet. Upon determining the cycle time using the method described above, earthmoving productivity can be estimated deterministically or using computer simulation, where the captured data for loading, hauling dumping and returning can be used to generate representative probability distribution; need to conduct the simulation process (Montaser et al, 2011). COMPARISON TO GPS TRACKING SYSTEM Both RFID and GPS are considered wireless technology. However, GPS utilizes satellite wireless communication and requires direct line of sight. Definitely, GPS can be used to track the location of hauling units, but the technology becomes costly for large number of hauling units as demonstrated in the economic analysis shown in Figure 5. The data used in the analysis is shown in Table 2. Assuming that, the dump area is serving one loading area. Number of Hauling Trucks = X RFID Reader Cost = C & RFID Tag Cost = R GPS unit Cost = G Table 2: Break-even point analysis Cost Element RFID System Cost in $ GPS System Fixed Cost: RFID Reader..(2C) 3, Variable Cost: RFID Tag (R) GPS Unit.(G) Total Cost 4X X Break Even Point (X) 8.2

8 1018 The figure below defines two ranges; one in which the use of RFID will be more economic and in the other, the use of GPS will be more economic. For the hypothetical data used in the example, the use of RFID will be more economical if the number of hauling units exceeds eight. If however, more than one loading area are serviced by one dumping area then the break even number of truck can be reduced. In the hypothetical example analyzed in this paper, the 8 trucks referred to above reduces to 6 when using two loading areas. Figure 5: Break-Even Point analysis between RFID and GPS based systems In addition to the potential economic advantage of RFID-based tracking system, described above, the system has further advantages. This advantage originally stems from the concept of the gate system, inherent in RFID technology, which can be used to track labor and material entering or exiting from the construction jobsite. RFID-based gate system can enhance real-time monitoring and progress reporting. RFID technology will also be more useful than GPS in tracking hauling units in dense downtown areas populated with high-rise buildings, which obstruct satellite signals SUMMARY AND CONCLUDING REMARKS Manual site data acquisition in earthmoving operations is time consuming and may result in tardy corrective actions with undesirable cost consequences. Radio frequency identification (RFID) has evolved to meet construction industry needs with its lower cost and increased

9 1019 capabilities. The developed method is a step ahead of regular RFID identification applications and expands upon its use in the construction industry. RFID + considered in this paper represents the traditional identification function of RFIDs plus the data fusion between RFID readers in the site and the dump area. The present study demonstrated the significance of data fusion between RFID readers. It presents practical and easy to use method for estimating productivity of earthmoving operations in near real-time. The example analyzed indicates that RFID technology could be more economical than GPS in cases where large number of hauling units is used. Near real time control of on-site earthmoving operations, facilitates early detection of discrepancies between actual and planned performances and support project managers in taking timely corrective measures. Incorporating RFID data in modeling earthmoving operations can be useful in tracking and control of earthmoving operations during execution of the work. REFRANCES Akinci, B., Patton, M., and Ergen, E. (2002). Utilizing radio frequency identification on precast concrete components-supplier's perspective. Proceedings of 19th International Symposium on Automation and Robotics in Construction (ISARC 2002), Washington, DC, 2002, Al-Ali, A. S. A., Sajwani, F., Al-Muhairi, A. and Shahenn, E. (2007). Assessing the feasibility of using RFID technology in airports. Proceedings of the 1st Annual RFID Eurasia, Eurasia Conference, Alkass, S., and Harris, F. (1988). Expert system for earthmoving equipment selection in road construction. Journal of Construction Engineering and Management, ASCE, 114(3), De la Garza, J. and Howitt, I. (1998). Wireless communication and computing at the construction jobsite. Journal of Automation in Construction, 7 (4), Ergen, E. and Akinci, B. (2007). An overview of approaches for utilizing RFID in construction industry. Proceedings of the 1st Annual RFID Eurasia, Eurasia Conference, Ergen, E., Akinci, B., and Sacks, R. (2007). "Tracking and locating components in a precast storage yard utilizing radio frequency identification technology and GPS." Journal of Automation in Construction, 16(3), Finkenzeller, K. (2010). RFID Handbook: Fundamentals and Applications in Contactless Smart Cards and Identification, John Wiley & Sons, 3rd edition. Fisher, J. A. and Monahan, T. (2008). Tracking the social dimensions of RFID systems in hospitals. International Journal of Medical Informatics March, 77(3), Goller, M.and Brandner, M., (2011). Experimental evaluation of RFID gate concepts. IEEE International Conference on RFID (IEEE RFID 2011), Goodrum, P., McLaren, M., Durfee, A. (2006). The application of active radio frequency identification technology for tool tracking on construction job sites. Journal of Automation in Construction, 15(3), Grau, D., and Caldas, C. (2009). "Methodology for automating the identification and localization of construction components on industrial projects." Journal of Computing in Civil Engineering, ASCE 23(1), Hajjar, D., and AbouRizk, S. (1999). Symphony: an environment for building special purpose simulation. 31st Winter Simulation Conference, ASCE, Phoenix, AZ, USA Intermec Solutions. Inc., (2011). RFID. < (Nov. 02, 2011).

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