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Applied Sciences
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Security Aspects and Energy Efficiency in Sensor Networks
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Security Aspects and Energy Efficiency in Sensor Networks

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: 20 January 2027 | Viewed by 1804

Editors

Prof. Dr. Krešimir Grgić

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Guest Editor
Department of Communications, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
Interests: security and privacy aspects of sensor networks; energy-efficient security mechanisms for sensor networks; advances in networking mechanisms for sensor networks; integration of sensor networks into other structures
Special Issues, Collections and Topics in MDPI journals
Dr. Višnja Križanović

E-Mail Website
Guest Editor
Associate Professor, Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
Interests: communication technologies assisted by sensors; advanced networking technologies assisted by sensors; performance evaluation of networking solutions with sensors
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Drago Žagar

E-Mail Website
Guest Editor
Faculty of Electrical Engineering, Computer Science and Information Technology, Josip Juraj Strossmayer University of Osijek, 31000 Osijek, Croatia
Interests: advanced networking technologies assisted by sensors; smart sensing; wireless communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, various types of sensor networks receive widespread use, and they represent one of the key foundations for the Internet of Things (IoT) paradigm. Sensor networks are integrated into different systems of critical importance in many aspects of human life and activity; therefore, it is important to adequately solve the issues of cyber security in these environments, which is a significant challenge due to the numerous limitations of sensor networks. The security aspects of sensor networks are closely related to energy efficiency issues; the primary reason for this due to the strict limitations on computing and energy resources, requiring security mechanisms designed for sensor networks to use these resources carefully and efficiently. This Special Issue aims to showcase a collection of technical papers from academia and industry that focus on topics including, but not limited to, the following:

  • Security and privacy aspects of sensor networks;
  • Energy-efficient security mechanisms for sensor networks;
  • Advances in networking mechanisms for sensor networks;
  • Integration of sensor networks into other structures.

Prof. Dr. Krešimir Grgić
Dr. Višnja Križanović
Prof. Dr. Drago Žagar
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensor networks
  • security aspects
  • energy efficiency
  • privacy
  • security mechanisms

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Published Papers (3 papers)

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Research

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37 pages, 6944 KB  
Article
Energy Savings in Public Lighting by Using Adaptive Street Lighting—A Framework for Energy-Savings Assessment and Machine Learning-Based Evaluation
by Višnja Križanović, Krešimir Grgić, Ana Pejković and Drago Žagar
Appl. Sci. 2026, 16(16), 7917; https://doi.org/10.3390/app16167917 (registering DOI) - 8 Aug 2026
Abstract
This study examines energy savings and efficient use through the application of smart adaptive lighting within the framework of “smart energy”, “smart city”, and “smart village”. Adaptive street lighting systems have emerged as an effective solution for reducing energy consumption while maintaining traffic [...] Read more.
This study examines energy savings and efficient use through the application of smart adaptive lighting within the framework of “smart energy”, “smart city”, and “smart village”. Adaptive street lighting systems have emerged as an effective solution for reducing energy consumption while maintaining traffic safety. However, existing studies typically evaluate energy performance under predefined traffic conditions or focus primarily on AI-based control strategies without systematically investigating the influence of object speed on energy savings. This study proposes a comprehensive methodology that combines CupCarbon traffic simulation, Shape-Preserving Cubic Hermite Interpolation (PCHIP), Monte Carlo simulation, sensitivity analysis, and machine learning to evaluate and predict the energy-saving performance of adaptive street lighting. Unlike previous approaches, the proposed framework establishes a continuous relationship between object speed and energy consumption, enabling the estimation of energy savings across the entire operating speed range while quantifying the effects of object speed, pole spacing, and pre-activation time. The machine learning models are employed to predict energy-saving results generated by the simulation framework. Six regression models were trained and validated using simulated datasets, with Gradient Boosting achieving the highest predictive accuracy. Moreover, the analysis demonstrated that adaptive street lighting scenarios operating at 50% power (50 W) under no-object conditions and 100% power (100 W) during object detection achieved energy savings of 19–37% per luminaire compared with conventional street lighting, depending on object speed. Furthermore, adaptive lighting operating at a constant 50% power (50 W) during object detection yielded substantially higher energy savings of 59–77% per luminaire, highlighting the significant influence of the lighting control strategy on overall energy efficiency. The results demonstrate that lower object speeds yield the greatest savings. The proposed methodology provides a robust and scalable framework for the design, optimization, and intelligent control of adaptive street lighting systems and offers a benchmark for evaluating the maximum theoretical energy-saving potential under controlled traffic conditions. Full article
(This article belongs to the Special Issue Security Aspects and Energy Efficiency in Sensor Networks)
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23 pages, 3569 KB  
Article
An Energy-Efficient Hybrid System Combining Sentinel-2 Satellite Data and Ground-Based Single-Pixel Detector for Crop Monitoring
by Josip Spišić, Davor Vinko, Ivana Podnar Žarko and Vlatko Galić
Appl. Sci. 2025, 15(24), 13241; https://doi.org/10.3390/app152413241 - 17 Dec 2025
Viewed by 741
Abstract
Precision agriculture will continue to heavily rely on data-driven models to enable more intensive crop monitoring and data-driven decisions. The available remote sensing techniques, particularly those based on multispectral Sentinel-2 data, still have major shortcomings due to cloud cover, low temporal resolution, and [...] Read more.
Precision agriculture will continue to heavily rely on data-driven models to enable more intensive crop monitoring and data-driven decisions. The available remote sensing techniques, particularly those based on multispectral Sentinel-2 data, still have major shortcomings due to cloud cover, low temporal resolution, and time lags in data availability. To address these shortcomings, this paper proposes a hybrid approach that combines Sentinel-2 satellite data with real-time data generated by low-cost ground-based single-pixel detectors (SPDs), such as the AS7263. This hybrid approach addresses key shortcomings in existing agricultural monitoring systems and offers a cost-effective, scalable solution for real-time monitoring and prediction of end-of-season yield, moisture, and plant height using simple PLRS models implemented directly in SPDs with an energy-efficient algorithm for deployment on the STM32G030 microcontroller. Full article
(This article belongs to the Special Issue Security Aspects and Energy Efficiency in Sensor Networks)
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Review

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35 pages, 1580 KB  
Review
A Review of Airport Security and Resilience Analysis: Integration of Risk Modelling Frameworks
by Lintong Li, Yunhao Li, Washington Yotto Ochieng, William Graham Proud, Mingyang Huang, Mireille El Hajj and Arnab Majumdar
Appl. Sci. 2026, 16(11), 5406; https://doi.org/10.3390/app16115406 - 28 May 2026
Viewed by 527
Abstract
Airports, as Critical National Infrastructure (CNI), operate as tightly coupled socio-technical systems exposed to multifaceted threats, including cyber, physical, social, environmental, and Chemical, Biological and Radiological (CBR) threats. This study presents a structured review of the synthesis of conceptual frameworks, airport structural configurations, [...] Read more.
Airports, as Critical National Infrastructure (CNI), operate as tightly coupled socio-technical systems exposed to multifaceted threats, including cyber, physical, social, environmental, and Chemical, Biological and Radiological (CBR) threats. This study presents a structured review of the synthesis of conceptual frameworks, airport structural configurations, sensor networks, and multi-domain threat landscapes, as well as airport security and resilience analysis, while comparatively examining risk assessment approaches. The review shows that existing approaches are effective for threat identification and prioritisation but remain predominantly static, with limitations in scalability, data dependency, and real-time applicability. To address these limitations, Threat-Vulnerability-Risk Assessment (TVRA) is adopted as a structured, reusable approach to support metric allocation, redundancy design, and emergency capability development. It further serves as a bridge between traditional risk assessment and resilience-oriented system design by enabling the transformation of static risk scores into scenario-based inputs, thereby supporting stress-testing and lifecycle-based resilience planning across the prepare, act, and recover phases. However, its inherently static structure limits its ability to capture temporal dynamics and cascading interdependencies, highlighting the need to integrate it with dynamic modelling approaches. Full article
(This article belongs to the Special Issue Security Aspects and Energy Efficiency in Sensor Networks)
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