In the field of mHealth, effective communication among
participants in the healthcare system is crucial for
achieving positive outcomes. Additionally, it facilitates
ongoing interaction between patients, healthcare
professionals, and digital health systems.
mHealth expands this area of communication beyond
traditional clinical interactions by including SMS
messages, online health forums, and continuous data streams
from wearable devices. These diverse communication channels
generate large amounts of unstructured, multimodal data
that require advanced computational methods for proper
interpretation. This survey explores different approaches
to language analysis and multimodal data processing within
the mHealth environment, along with available resources and
open research challenges. These challenges include the lack
of annotated corpora for Serbian (a low-resource language),
data interoperability issues, and concerns related to
privacy and ethics.
The focus is on natural language processing (NLP)
techniques, including sentiment analysis, text
classification, and named entity recognition, applied to
user-generated content such as SMS messages, online forum
discussions, and electronic health records (EHRs). These
methods enable the extraction of valuable insights from
large volumes of unstructured textual data, facilitating
health monitoring, early detection of pathological
conditions, and improved patient engagement. Data collected
from wearable devices provide valuable physiological and
contextual information, further enriching communication
streams and supporting more accurate and personalized
health assessments. Particular attention is given to the
challenges of analyzing informal and highly variable
language characteristic of technology-mediated discourse,
including the use of slang, abbreviations, and non-standard
spelling in Serbian. Semantic analysis, combined with NLP
techniques, can help identify ambiguities, unclear
formulations, contradictory statements, and other semantic
errors.
The importance of communication as a fundamental component
of the healthcare system is emphasized, as is the potential
to integrate NLP techniques with wearable device data to
develop scalable, adaptive, and personalized healthcare
solutions. Effective communication analysis can enhance
decision-making processes and optimize mHealth
interventions.
The integration of language analysis and sensor data for
the development of advanced, personalized mHealth
solutions, along with improved capabilities for real-time
understanding of user behavior and health status,
represents a promising direction for future research and
highlights the need for further investigation and
standardization in this domain.

Abstract
This paper explores the fundamental concepts of Blockchain
technology, its various forms, methods and areas of
application, as well as the advantages and limitations
associated with its use. In addition, the paper discusses
possible directions for the future development of
Blockchain systems. The main objective is to introduce
readers with little or no prior knowledge to the core
principles of Blockchain technology and to provide guidance
in selecting the most suitable type of Blockchain for
specific applications.

Therefore, we will introduce a completely new way of
applying this technology in the creation of digital
currency based on art.
Because of the increasing popularity and broad range of
applications of Blockchain technology, the number of
related studies and articles has grown significantly. As a
result, it may be challenging for readers to identify the
most relevant direction when exploring specific topics.
This paper therefore aims to assist readers in selecting an
appropriate path for further research while also presenting
new perspectives on the potential use of Blockchain
technology.

For the authors, this paper represents an initial step
toward addressing challenges in Blockchain systems through
optimization techniques supported by artificial
intelligence, as well as exploring the use of this
technology in building a sustainable value system.

During coal combustion in thermal power plants, harmful
substances such as sulfur oxides, nitrogen oxides, as well
as CO₂, and fine particulate matter are released.
Additionally, wastewater is generated along with residual
materials in the form of fly ash and slag. Fly ash consists
of fine inorganic particles separated from flue gases by
electrostatic precipitators, while larger particles settle
as slag. The quantity and characteristics of fly ash and
slag depend on the coal composition and the combustion
technology used. They are disposed of in landfills near
thermal power plants when not considered useful, leading to
soil contamination, heavy metal leaching into the food
chain, and atmospheric dispersion of fine ash particles,
posing risks to ecosystems and human health. This
represents a more than sufficient argument for the
increasing focus on their potential applications aimed at
reducing environmental impacts and enhancing the value of
these industrial residues. Their use in the construction
industry, especially as an additive or partial substitute
for cement in concrete, reduces CO₂ emissions and helps
protect the environment. Using fly ash in building roads,
bridges, dams, and even large high-rise structures shows
that industrial residues can become sustainable materials
with considerable economic and environmental benefits.

Digitalizacija u zdravstvu, podržana primenom tehnologija
veštačke inteligencije (AI) i Interneta stvari (IoT), nudi
značajne mogućnosti za poboljšanje dijagnostike, praćenja
pacijenata i optimizaciju medicinskih procesa. Microsoft
Azure platforma pruža širok spektar rešenja koja
omogućavaju zdravstvenim ustanovama da integrišu AI i IoT
tehnologije kako bi se poboljšao kvalitet nege i povećala
operativna efikasnost. U ovom radu ispituju se načini na
koje se veštačka inteligencija i IoT tehnologije, podržane
Microsoft Azure platformom, mogu primeniti u optimizaciji
zdravstvenih usluga kroz analizu podataka
kardiotokografije. Posebna pažnja posvećena je primeni
ovih tehnologija u praćenju vitalnih parametara
pacijenata, prediktivnoj analitici i poboljšanju operativne
efikasnosti zdravstvenih ustanova. Razmatraju se izazovi i
ograničenja povezana sa implementacijom ovih tehnologija,
kao i potencijalna rešenja za njihovo prevazilaženje.
Prikazani su konkretni primeri primene, sumirani su ključni
nalazi i razmatrane su buduće perspektive razvoja u ovoj
oblasti.

Čista energija u funkciji zelene gradnje je ključni koncept
savremene arhitekture i urbanizma. Ona se oslanja na
obnovljive izvore energije i uz primenu principa zelene
gradnje, značajno doprinosi smanjenju negativnih uticaja na
životnu sredinu i povećanju energetske efikasnosti
objekata. Korišćenje obnovljivih izvora povećava održivost
zgrada, smanjuje operativne troškove i poboljšava ekološki
otisak, čime direktno podržava koncept zelene gradnje i
održivog urbanog razvoja. Investiranje u zelenu gradnju bi
trebalo da znači dugoročnu uštedu energije i novca, kao i
podstrek razvoju lokalne energetske infrastrukture. U radu
se razmatra značaj integracije ovih pristupa i ukazuje na
njihove prednosti u unapređenju energetske efikasnosti i
kvaliteta života. Zelena gradnja predstavlja važan korak ka
održivom razvoju i zaštiti životne sredine, a primena čiste
energije je njen osnovni element.

Rad će dati pregled okvira za procenu buke u železničkom
okruženju (vozila). Posebno će se komentarisati tehničke
specifikacije za interoperavilnost za smanjenje buke, ali
sa stanovišta postavke opreme za merenje, u skladu sa
preporučenim okvirima, regulativom i standardima.