Ivana Šenk |
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A model for product localization based on Internet of Things technologiesMy PhD research was dealing with localization of products (boxes in the experiments) based on Internet of Things technologies, focused on RFID technology and wireless sensor networks.
I applied different localization methods - multilateration, weighted k-NN, a novel method based on particle swarm optimization, and a novel method based on a particle filter. I have then set a model for product localization, where I presented and implemented a hybrid localization method based on data fusion of weighted k-NN and particle swarm optimization based localization methods, and additional data fusion of the data from the RFID system and the wireless sensor network. One of the goals of my dissertation was to show that the data fusion of different localization methods and of different localization technologies will lead to increased localization accuracy and precision. The proposed methods were all implemented and tested in two test beds, in a classroom and on a test assembly line in our university laboratory. Based on the results, it was concluded that the proposed hybrid method provides localization accuracy and precision parameters that are either better or at least on the same level as the best parameters gained by other methods, which shows that the proposed localization system is more reliable than the systems that implement only one method or one technology. |
Application of automatic identification technologies for food product traceability Research on food product traceability was dealing with the possibilities of tracking food from raw food production through processing, transport and retail to the end consumer, as well as with the possibilities of tracing food products back through all these steps to its origin. We researched the need for tracking the specific data, such as the place of origin, date of production, allergens, etc. and proposed the key data that should be recorded in every step of the process. The most important part of this research was experimenting with different automatic identification technologies. RFID and 2D barcodes were chosen for different stages of the food production as they give the best advantages/disadvantages ratio - they allow faster data acquisition, recording and reading processes than the traditional means, and provide up-to-date information in each product stage. Furthermore, these technologies allow the possibility to record large amounts of data for each specific product, and store all data in a database.
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Cattle monitoring based on RFID technologyCattle identification and monitoring on small cattle farms are usually based on barcode technology or by hand. This kind of identification is unsuitable for dairy cows milking and feeding process automation. So we researched the application possibilities of RFID technology. We used a UHF RFID system operating at 915 MHz, while the RFID tags were glued onto the standard dairy cow ear labels. The system was developed and implemented as a test bed at a small cattle farm in Serbia.
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Access controlThe research on access control was focused on implementation of RFID technology and/or mobile phone's WiFi for monitoring the attendance at a conference or for monitoring the students attendance at lectures or in a lab. The conference attendance system was implemented with two RFID readers facing in and out of the conference room. Each participant was carrying an RFID name tag, which was then scanned by the readers, and the system determined when someone entered or exited the room. The student attendance system was implemented as a phone application, that automatically registers the student's attendance when they are connected to the WiFi network in the classroom. Another implementation uses RFID technology for the door lock that allows the students to access the lab and use the equipment for experiments throughout the day.
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