Milan Vidaković

The future of health care is evolving toward artificial intelligence (AI)-driven personalized regenerative systems. This article explores the future trajectory of a hybrid AI-powered regenerative health care ecosystem enabling real-time self-learning health-care solutions through AI-driven decision support, neuroadaptive exoskeletons, biostimulatory wearables, drug delivery, and self-regulating smart implants.

In recent years, home energy management systems (HEMSs) have emerged as critical components within the concept of smart cities and grids. Within HEMSs, load flow analysis represents one of the fundamental tools for smart grid studies, forming the basis for a wide range of advanced applications, including state estimation, fault diagnosis, and optimal power flow computation. To achieve high levels of load flow accuracy and reliability, HEMSs must incorporate detailed models of all electrical elements found in modern residential units, including appliances, wiring, and energy resources. This paper proposes a load flow solution for smart home networks, featuring detailed models of wiring, appliances, and on-site generation systems. Moreover, a detailed appliance model derived from smart meter data, capable of representing both static-load devices and complex appliances with time-varying consumption profiles, is introduced. Additionally, a measurement-based validation of residential electrical wiring model is presented. The proposed models and calculation procedures have been verified by comparing the simulated results with the literature, yielding a deviation of approximately 0.7%. Analyses of a large-scale network have shown that this approach is up to six times faster compared to state-of-the-art procedures. The developed solution demonstrates practical applicability for use in industry-grade smart power management software.

In this paper, we propose an abstract domain-neutral architecture for a cognitive digital twin (CDT) and a software platform to develop such CDTs, including machine reasoning capabilities. Sustainable development refers here to an abstract model that enables a holistic view of limiting resources and has an ability to adapt to different application domains while reusing existing resources. The proposed solution allows for a unified abstract representation and the development of a wide range of diverse digital twins, as well as facilitating their interoperability. The abstract architecture consists of a four-layer structure (observation/actuation layer, data management layer, reasoning layer, and simulation layer) with an upper ontology to which the domain ontology of the specific CDT is mapped. The architecture relies on semantic web technologies, including ontology-based reasoning using OWL, and a loosely coupled, component-based service-oriented software architecture. The platform utilizes a microservice architecture that enables separate, loosely coupled services on each layer, message queues to provide asynchronous communication, and possesses cloud technologies to achieve scalability. The proposed approach was validated by implementing a software platform prototype and demonstrating its key features through two dissimilar scenarios. The first scenario demonstrates simple sustainable energy management through IoT systems inside smart buildings, while the second one demonstrates knowledge quality management based on knowledge space theory.

This article presents one experience with the design and implementation of a consumer electronics (CE) software module using automotive software process improvement and capability determination (A-SPICE) methodology. Electronic program guide (EPG) engine software module is a very stable, configurable product that ensures high performance and satisfies different television standards. It is designed to operate on a wide range of hardware platforms, especially in automotive multimedia systems. Since the EPG engine had to be integrated into the automotive infotainment system, that module was developed in compliance with the Hersteller Initiative Software-Manufacturer's software initiative metrics and A-SPICE standard. Application lifecycle management tool was used in the development process for project management and for generating data for analysis purposes. The software itself was tested during the whole project lifecycle using several static and dynamic code analysis methods. Difficulties concerning testing procedures, code quality, and complying with A-SPICE standard were detected and resolved. Since the CEs software development is not that strict as automotive one, this article points out the advantages of introducing the A-SPICE methodology in the CE field.