Precise time interval generation is a cornerstone of modern measurement, automation, and distributed control systems, particularly within Internet of Things (IoT) architectures. This paper presents the design, implementation, and evaluation of a low-cost and high-precision time interval generator based on Complementary Metal-Oxide Semiconductor (CMOS) logic counters (Integrated Circuit (IC) IC 7493 and IC 4017) and inverter-based crystal oscillators (IC 74LS04). The proposed system enables frequency division from 1 MHz down to 1 Hz through a cascade of binary and Johnson counters, enhanced with digitally controlled multiplexers for output signal selection. Unlike conventional timing systems relying on expensive Field-Programmable Gate Array (FPGA) or Global Navigation Satellite System (GNSS)-based synchronization, this approach offers a robust, locally controlled reference clock suitable for IoT nodes without network access. The hardware is integrated with Arduino and ESP32 microcontrollers via General-Purpose Input/Output (GPIO) level interfacing, supporting real-time timestamping, deterministic task execution, and microsecond-level synchronization. The system was validated through Python-based simulations incorporating Gaussian jitter models, as well as real-time experimental measurements using Arduino’s micros() function. Results demonstrated stable pulse generation with timing deviations consistently below ±3 µs across various frequency modes. A comparative analysis confirms the advantages of this CMOS-based timing solution over Real-Time Clock (RTC), Network Time Protocol (NTP), and Global Positioning System (GPS)-based methods in terms of local autonomy, cost, and integration simplicity. This work provides a practical and scalable time reference architecture for educational, industrial, and distributed applications, establishing a new bridge between classical digital circuit design and modern Internet of Things (IoT) timing requirements.

Air transport is a key driver of economic development, tourism, and regional connectivity, yet its growth generates increasing environmental costs. Grounded in the catalytic effects framework and the sustainability trade-off perspective, this exploratory study examines the economic and sustainability dimensions of air traffic recovery and growth at Belgrade Nikola Tesla Airport during 2019–2024, a period encompassing a pandemic shock and record post-pandemic expansion. Descriptive statistical analysis and Pearson correlation analysis were applied to six annual data points, supplemented by an approximate CO₂ emission estimation. Passenger traffic increased from 6.16 to 8.37 million (+35.9%), and the destination network expanded from 99 to 135 routes. A positive co-movement was observed between passenger traffic and foreign tourist arrivals (r = 0.970; p = 0.001). No detectable association was found between passenger traffic and annual GDP growth rate (r = 0.143; p = 0.79). Estimated CO₂ emissions grew proportionally from 0.831 to 1.130 million tonnes, consistent with the proportional growth pattern generated by the fixed-factor estimation framework applied. The passengers-per-movement ratio improved from 87.5 to 97.2, indicating a proximate improvement in operational efficiency. These preliminary findings provide exploratory evidence relevant to Sustainable Development Goals 8 and 9 and may inform future research and policy discussions on the sustainability dimensions of airport development.