This paper presents an end-to-end architecture for smart waste management, leveraging real-time data, IoT, AI, and machine learning to optimize operational efficiency and decision-making processes. The architecture is designed for both near real-time and batch data processing, ensuring continuous optimization and adaptation of waste collection routes and resource allocation. Machine learning models are employed to predict possible bad adverse scenarios and optimize operational plans. Additionally, business intelligence is utilized for data analysis and reporting, providing actionable insights based on real-time and historical data. The presented system is implemented on a scalable Kubernetes infrastructure, supporting the increasing data volumes and processing demands while maintaining system responsiveness and efficiency. This integrated approach demonstrates significant improvements in resource utilization, operational efficiency, and service delivery, highlighting the potential for smarter and more sustainable waste management practices. This research addresses the gap in combining IT architectures with AI models and IoT, paving the way for future advancements in smart waste management systems.

This article presents a simple software-developed model for calculating the relative frequency of individual symbols and the entropy of the Latin alphabet of a standardised language used by four South-Slavic origin ethnic groups in the Western Balkans in four countries. In addition, a method of applying the Shannon-Fano and Huffman source coding algorithms is presented, which takes into consideration the specificity of the observed alphabet in relation to the English one. The presented model is developed in the MATLAB programming language. The model is tested using an arbitrarily selected text.

This paper presents a model that enables the application of smart waste collection management using artificial intelligence to detect QR-codes on the video stream of surveillance cameras attached to waste collection trucks. A framework model proposal together with a detailed explanation of the key components of the system is shown. It also demonstrates the use of QR-code detection for identification of waste bins and its specific application in smart waste management system.

The aim of the paper is the quality of video streaming analysis in cases of using different video codecs in the environment of distributed computer systems with different QoS (Quality of Service). For the purposes of the analysis, several scenarios were set up in which video encoded with different codecs is transmitted by a virtual video streaming server to virtual clients. For each of the scenarios, an environment with different QoS (packet losses, latency, jitter) was simulated and the quality of the received video stream was evaluated for each video codec. The quality of the received decoded video stream was calculated using SSIM (Structural Similarity) and VMAF (Video Multimethod Assessment Fusion) video objective metrics and compared to the original video stream.

In this study, the implementation of Free Route Airspace (FRA) in Europe is presented, with special reference to the merge of SECSI FRA (South East Common Sky Initiative Free Route Airspace) and FRA IT(Free Route Airspace in Italy) in to the SECSI IT FRA. Free Route Airspace is a certain volume of airspace in which users are free to plan a route between defined entry and exit points. Depending on the availability of airspace, routing is possible via waypoints, without calling the Air Traffic Service (ATS) route network. The purpose of this paper is to show how the implementation of free route airspace in Europe, affects traffic indicators in terms of flight length, fuel consumption, environmental impact and economy. This paper will also show a slight decrease in air traffic controller load as a result of the implementation of free route airspace. We also wanted to show how, the merge of SECSI FRA and FRA IT, affects Bosnia and Herzegovina airspace. When fully implemented at European level, it should allow the following savings, compared to the current situation: 1 billion nautical miles in terms of flight length, 6 million tons of fuel savings, and 5 billion euros less costs in in terms of fuel savings.

The increased volume of initiatives and investments in the framework of smart cities, as well as strong investments in AI/ML technology together with the IoT industry, undoubtedly represent the future of practical activities and the implementation of new generation technological solutions in cities. By analyzing the previous literature and related works, in the field of smart waste management solutions, the focus of research was placed on isolated problems at lower levels of technology implementation on individual subsystems with individual environments. The purpose of this paper is to emphasize the need for a systematic integrated approach in the process of designing a model of practical application of technology to solve the problem of waste management in cities with a special aspect on business processes and the end user. The paper presents an analysis of related works and commercial solutions implemented so far and proposes a practical implementation model that, among other things, includes a component of a higher level of abstraction that should perform an additional iteration of the AI/ML process and make a final decision in the prediction process and controls in smart waste management solutions.

This paper depicts a practical implementation of business model created by Centre for digital communications with customers of ALBA company and the framework of using cloud system in supporting that model. Software implementation includes Web and mobile applications for customers as well as control panel for software administration by company employees. The uniqueness of the implementation is reflected in the advanced geolocation services that include the generation of content according to the user needs based on the selected location of the city or settlements. The model also includes opportunities for further development with the use of IoT technologies to manage the waste disposal process.