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.

                                                          Concurrent and Distributed Modeling   This post will cover thoughts and idea...