Inteli-Straw (I-S) devices equipped with radiofrequency identification (RFID) technology were developed for gamete and embryo packaging, storage, and information retrieval to benefit the assisted reproduction industry. The aim of this study was to develop and test software for use with I-S technology. Two types of I-S were used, those with 125 and 134 kHz RFID chips, in conjunction with corresponding wireless RFID readers. Two different RFID chip designs were tested: (1) Mini: 0.25-mL straw, RFID tag dimensions = 1.25 × 7 mm and 1.4 × 8 mm; Standard: 0.5-mL straw, RFID tag dimensions = 2 × 12 mm; and (2) µ-chip (Hitachi Ltd., Tokyo, Japan) of 0.4 mm square and 0.06 mm thick. Inteli-Straw RFID chips can be written or have codes that can be associated with information in a database. The present RFID chips were used with the idChamp DX1 Veterinary & Livestock RFID Reader that uses Bluetooth to connect to an iOS platform for cloud computing. The iScanBrowser (Serialio, TX, USA) LED, an app for an iOS platform for use with a wireless RFID reader, was utilised, as well as a proprietary gamete and embryo database software. The present system allows for quickly accessing the RFID codes from the various I-S gamete and embryo packaging (before or after I-S filling) and entering the data into a computer or cloud-based database that can track their status, movement, metadata, and so on. The ability to acquire I-S information with wireless entry into the cloud-based database was achieved. When the RFID wireless reader detects an I-S, the RFID code is displayed almost immediately (~1 s) in a cell in the software system. The I-S (n = 194) were scanned for automatic database entry. For the wireless-enabled proof of concept, 17 scans of I-S [i.e. RFID chip design 1 (n = 15) and design 2 (n = 2)] were made with wireless scanner detection (< 2.5 cm from RFID reader to I-S) and online database entry with a 100% success rate. By using this I-S method, the present invention provides a wireless, cloud-based system for local or remote access, potentially benefiting both laboratory and field logistics. For AI and embryo transfer, the user can scan an I-S and the information is automatically detected; wireless cloud computing and RFID data crosschecking can occur; and the information can be uploaded to a database for later retrieval or analysis. Further, one can use an iphone or ipad to enter other information such as cow number into the cloud-based database during AI or embryo transfer. The present system can allow for near real-time viewing of the data, locally and remotely, or cross-checking of materials and associated information to reduce errors and improve assisted reproductive technology efficiency.
Empirical Investigation of TCP Incast Congestion in Wireless Cloud Computing Networks