No abstract

The Internet of Things (IoT) is built on a strong internet infrastructure and many wireless sensor devices. Presently, Radio Frequency Identification embedded (RFID-embedded) smart cards are ubiquitous, used for many things including student ID cards, transportation cards, bank cards, prepaid cards, and citizenship cards. One example of places that require smart cards is libraries. Each library, such as a university library, city library, local library, or community library, has its own card and the user must bring the appropriate card to enter a library and borrow material. However, it is inconvenient to bring various cards to access different libraries. Wireless infrastructure has been well developed and IoT devices are connected through this infrastructure. Moreover, the development of biometric identification technologies has continued to advance. Blockchain methodologies have been successfully adopted in various fields. This paper proposes the BlockMetrics library based on integrated technologies using blockchain and finger-vein biometrics, which are adopted into a library collection management and access control system. The library collection is managed by image recognition, RFID, and wireless sensor technologies. In addition, a biometric system is connected to a library collection control system, enabling the borrowing procedure to consist of only two steps. First, the user adopts a biometric recognition device for user authentication and then performs a collection scan with the RFID devices. All the records are recorded in a personal borrowing blockchain, which is a peer-to-peer transfer system and permanent data storage. In addition, the user can check the status of his collection across various libraries in his personal borrowing blockchain. The BlockMetrics library is based on an integration of technologies that include blockchain, biometrics, and wireless sensor technologies to improve the smart library.

No abstract

This paper proposes a fusion model that merges the context-aware multimodal information of JADE (Java Agent DEvelopment Framework). The context-aware multimodal information system is developed from the multi-heterogeneous context sensing devices. This multimodal not only gathers multidimensional data that aims to recognize and analyze the collected emotion information, but also emotion manages the context-aware information. According to the collections of users use remote control usages during watching TV and the face recognition technology, we developed a context-aware multimodal information system to recognize emotions. The emotion information is reasoned from the action data of remote control usages that combines with the emotion information gathered from the face recognition. These two information fuses with the feedback mechanism of real emotion to acquire the information of personal emotion representation. This fusion model of context-aware multimodal information provides personal emotion information and learning mechanism to reason the information from contextaware ubiquitous environment applied on personal emotion prediction.

No abstract