Friday, January 7, 2022
Monday, January 3, 2022
Computer Assisted Design building the RFID Key Cyber Terrain
Multiple industries that have deployed RFID in the past suggest that more than 98% of RFID design activity comprises recurring redundant configuration changes. However, despite the importance of RFID deployment, implementation, and change management design activities, researchers have estimated that 95% of companies have no systematic approaches to preventing RFID deployment procedures that facilitate indefinite repeat.
Problem Domain
Many companies have no idea where to start after deciding that an RFID solution is a technology they want to employ. Even after companies accomplish comprehensive requirements assessments, many find out that their vendor's technology or product has limits. Requiring the vendor to accommodate your dynamic needs increases TCO (total cost of ownership), not just the initial buying price. But you are most likely thinking, "I can seek guidance from independent experts to support my efforts in areas where I need assistance." But even acquiring experts will still cost you money and time (and possibly a few headaches) if you or your company is lacking knowledge of RFID Unfortunately, with many RFID solutions on the market today, it's rare to find any with the ability to negotiate change. Whether it is changing infrastructure location and size, paradigms, tracking area footprint, transitory asset trends, employees (think knowledge management), and network topologies, to name a few. Sound predictions of RFID performance are now a necessity if companies are to cope with unforeseen changes. Still, they must understand the range of forecasting possibilities available from the RFID vendor or their products. ProxiTrak has a unique functionality that can organize RFID data to align with a predictive model so companies can forecast RFID coverage performance and outputs for hypothesis tests (Motamedi, Setayeshgar, Soltani, & Hammad, 2013). The prediction designer is based upon the availability of historical data and the degree of zone accuracy desirable, among other factors like antenna/tag RSSI strength. Predictive Analytics ProxiTrak uses historical data to predict future RFID events that affect health. Plan, Predict, Act on Change ProxiTrak utilizes historical data in concert with the CAD model that captures essential trends. That predictive model is then used to adjust the correlation of hardware functionality between the virtual and real world.
References
Costin, A., Pradhananga, N., & Teizer, J. (2012).
Integration of passive RFID location tracking in building information models
(BIM). Paper presented at
the EG-ICE, Int. Workshop, Herrsching, Germany.
Costin, A., Pradhananga, N., & Teizer, J. (2014).
Passive RFID and BIM for real-time visualization and location tracking. Paper
presented at the
Construction Research Congress 2014: Construction in a
Global Network.
Costin, A. M., & Teizer, J. (2015). Fusing passive RFID
and BIM for increased accuracy in indoor localization. Visualization in
Engineering, 3(1), 17.
Costin, A. M., Teizer, J., & Schoner, B. (2015). RFID
and BIM-enabled worker location tracking to support real-time building protocol
and data
visualization. Journal of Information Technology in
Construction (ITcon), 20(29), 495-517.
Li, C. Z., Zhong, R. Y., Xue, F., Xu, G., Chen, K., Huang,
G. G., & Shen, G. Q. (2017). Integrating RFID and BIM technologies for
mitigating risks and
improving schedule performance of prefabricated house
construction. Journal of Cleaner Production, 1 65, 1048-1062.
Motamedi, A., Setayeshgar, S., Soltani, M., & Hammad, A.
(2013). Extending BIM to incorporate information of RFID tags attached to
building assets.
Paper presented at the International Conference on Computing
in Civil and Building Engineering, Montreal, Canada.
Xie, H., Shi, W., & Issa, R. R. (2010). Implementation
of BIM/RFID in computer-aided design- manufacturing-installation process. Paper
presented at the
2010 3rd International Conference on Computer Science and
Information Technology.
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