In this paper, an overlapping-resistant Internet of Things (IoT) solution for a Bluetooth Low Energy (BLE)-based indoor tracking system (BLE-ITS) is presented. The BLE-ITS is a promising, inexpensive alternative to the well-known GPS. It can be used in human traffic analysis, such as indoor tourist facilities. Tourists or other customers are tagged by a unique MAC address assigned to a simple and energy-saving BLE beacon emitter. Their location is determined by a distributed and scalable network of popular Raspberry Pi microcomputers equipped with BLE and WiFi/Ethernet modules. Only simple triggered messages in the form of login records (LRs) are sent to a server, where the so-called path vectors (PVs) and interest profile (IPr) are set. The authors implemented the prototype and demonstrated its usefulness in a controlled environment. As it is shown in the paper, the solution is highly overlap-resistant and mitigates the so-called multilocation problem.

Nowadays, one of the key areas of research on contact centre systems is their automation. The main element that influences the possibility of automation of contact centre processes is the call transcription methods implemented by automatic speech recognition (ASR) systems. Such systems enable developing intention recognition methods and, consequently voice bots. The current solutions used in ASR systems for many less popular languages do not guarantee a fully satisfactory transcription quality for hotline voice calls. This is due to the unique characteristics of the sound signal generated there, whose quality parameters differ significantly from those of studio recordings. The paper presents a comparative study of selected speech recognition systems that were additionally supplemented with elements of preprocessing of sound recordings and postprocessing of originally produced transcriptions. As for preprocessing, the following methods were tested: separation of the client and agent channels into two independent signals, training of ASR systems, and audio signal correction. With regards to postprocessing, on the other hand, tests were performed for inarticulate sounds, normalization of standard phrases (e.g. numbers, dates, times, etc.), and identification of close-sounding phrases and foreign language phrases, and lemmatization. Based on the research conducted and the analyses performed, a new method of call transcription intended specifically for contact center systems was proposed. The research conducted for this paper was based on the Polish language model, for which major problems are observed with the quality of automatic contact center call transcriptions.

Introducing a strong consistency model into NoSQL data storages is one of the most interesting issues nowadays. In spite of the CAP theorem, many NoSQL systems try to strengthen the consistency to their limits to better serve the business needs. However, many consistency-related problems that occur in popular data storages are impossible to overcome and enforce rebuilding the whole system from scratch. Additionally, providing scalability to those systems really complicates the matter. In this paper, a novel data storage architecture that supports strong consistency without loosing scalability is proposed. It provides strong consistency according to the following requirements: high scalability, high availability, and high throughput. The proposed solution is based on the Scalable Distributed Two–Layer Data Store which has proven to be a very efficient NoSQL system. The proposed architecture takes into account the concurrent execution of operations and unfinished operations. The theoretical correctness of the architecture as well as experimental evaluation in comparison to traditional mechanisms like locking and versioning is also shown. Comparative analysis with popular NoSQL systems like MongoDB and MemCached is also presented. Obtained results show that the proposed architecture presents a very high performance in comparison to existing NoSQL systems.