Aigul Skakova

Dr. Aigul Skakova


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 May 2026 in Electronics
Verified
Journal Article
Open access
PDF file
SMSaken Mambetov
Saken Mambetov
DNDinara Nurpeissova
Dinara Nurpeissova
KTKyrmyzy Taissariyeva
Kyrmyzy Taissariyeva
GTGulnara Tleuberdieva
Gulnara Tleuberdieva
Zhanna MukanovaZhanna Mukanova
Zhanna Mukanova
ASAigul Skakova
Aigul Skakova
The rapid deployment of 5G networks and the proliferation of Internet of Things (IoT) devices have significantly increased the complexity of urban electromagnetic radiation (EMR) environments. Conventional ground-based monitoring systems are spatially limited and unable to provide three-dimensional field characterization. This paper proposes an integrated IoT–UAV framework for high-resolution EMR monitoring, spatial reconstruction, and intelligent source classification. A four-layer architecture combining distributed sensing, edge computing, cloud analytics, and visualization is developed. A formal electromagnetic propagation model is introduced to ensure consistency between broadband exposure measurements and frequency-selective spectral analysis. A CNN–LSTM architecture is implemented for spectral–temporal source classification, achieving 95% validation accuracy across five EMR categories. Simulation-based validation demonstrates up to an eightfold improvement in spatial coverage compared to fixed ground networks while maintaining a practical anomaly detection threshold of −55 dBm in the spectrum-analysis RF chain. The proposed framework establishes a mathematically consistent and practically deployable solution for next-generation EMR monitoring systems.

30 September 2026 in EKTU Journal of Information and Communication Sciences
Verified
Journal Article
Open access
PDF file
SISulu Issabayeva
Sulu Issabayeva
ASAigul Skakova
Aigul Skakova
GAGulnar Astaubayeva
Gulnar Astaubayeva
BZBimoldina Zharkyn
Bimoldina Zharkyn
BNBilimzhankyzy Nazerke
Bilimzhankyzy Nazerke
Thearticle examinesthe developmentof artificialintelligence andbig datatechnologies inthe Republicof Kazakhstanwithin theframework ofthe digitaltransformation ofpublic administration. The relevanceof thestudy isdetermined bythe needto enhancethe targetingof socialpolicy andto improvethe efficiencyof publicservice deliverythrough theanalysis oflarge-scalesocio-demographicdata sets. The aimof theresearch isto assessthe potentialof applyingintelligent algorithmsand bigdata processingtools inthe analysisof theDigital FamilyMap asa componentof thestate informationinfrastructure. Thestudy employssystemic andinstitutional analysis, a comparativeapproach, andelements ofapplied dataanalytics. Thefindings identifykey directionsfor integratingintelligent technologiesinto publicdecision-makingprocesses andsubstantiate theiradvantages interms offorecasting accuracyand resourceoptimization. Thescientific noveltylies inthe comprehensiveassessment ofintegrating intelligentdata analysistechnologies intothe socialsphere, whilethe practicalsignificance isreflected inthe potentialto improvemechanisms fordelivering publicservices.