Featured Application: The proposed hybrid environmental monitoring framework provides a reproducible methodology for integrating professional fixed monitoring stations with autonomous mobile sensing platforms through reference-based calibration, heterogeneous data fusion, and spatial interpolation. The framework enables the generation of spatially consistent environmental information while preserving the measurement reliability of fixed reference stations. Although experimentally validated within a hospital campus, the methodology is applicable to a wide range of complex outdoor environments characterized by distributed infrastructures and repeated operational routes, including industrial campuses, logistics hubs, freight terminals, airports, and port facilities. By addressing the upstream challenges of data quality, reference-based calibration, and heterogeneous sensing integration, the proposed approach provides a reproducible sensing methodology that can serve as a reliable foundation for future environmental monitoring systems and higher-level cyber-physical platforms, that may support future environmental Digital Twins and intelligent decision-support systems. Hybrid environmental monitoring systems combining fixed and mobile sensing platforms are increasingly attracting attention for the characterization of complex outdoor environments. However, the practical integration of heterogeneous sensing infrastructures remains challenging because measurement consistency, sensor calibration, data fusion, and spatial reconstruction are often addressed separately rather than within a unified monitoring methodology. This work presents a hybrid environmental monitoring framework that integrates professional fixed monitoring stations with an autonomous ground vehicle equipped with low-cost environmental sensors. The proposed methodology combines reference-based calibration, temporal alignment, heterogeneous data fusion, and spatial interpolation to generate spatially consistent environmental information from complementary sensing platforms. The proposed methodology is experimentally validated through a monitoring campaign conducted within the IRCCS Policlinico San Martino hospital campus (Genoa, Italy), where repeated mobile measurements were integrated with two professional monitoring stations along a 350 m outdoor route characterized by heterogeneous environmental conditions. The calibration procedure significantly improved the agreement between fixed and mobile observations, while the comparative analysis of four interpolation techniques demonstrated that interpolation performance depends on the spatial distribution of measurements and the characteristics of the monitored environmental field rather than on the intrinsic superiority of a specific algorithm. The results further demonstrate the feasibility of integrating fixed and mobile sensing into a coherent and reproducible environmental monitoring workflow. Although validated in a hospital environment, the proposed methodology is applicable to other complex outdoor scenarios featuring distributed infrastructures and repeated operational routes, including industrial campuses, logistics hubs, freight terminals, airports, and port facilities.
Environmental Monitoring for Smart Logistics: A Hybrid Mobile–Fixed Sensor Fusion Framework
Elvezia Maria Cepolina;
2026-01-01
Abstract
Featured Application: The proposed hybrid environmental monitoring framework provides a reproducible methodology for integrating professional fixed monitoring stations with autonomous mobile sensing platforms through reference-based calibration, heterogeneous data fusion, and spatial interpolation. The framework enables the generation of spatially consistent environmental information while preserving the measurement reliability of fixed reference stations. Although experimentally validated within a hospital campus, the methodology is applicable to a wide range of complex outdoor environments characterized by distributed infrastructures and repeated operational routes, including industrial campuses, logistics hubs, freight terminals, airports, and port facilities. By addressing the upstream challenges of data quality, reference-based calibration, and heterogeneous sensing integration, the proposed approach provides a reproducible sensing methodology that can serve as a reliable foundation for future environmental monitoring systems and higher-level cyber-physical platforms, that may support future environmental Digital Twins and intelligent decision-support systems. Hybrid environmental monitoring systems combining fixed and mobile sensing platforms are increasingly attracting attention for the characterization of complex outdoor environments. However, the practical integration of heterogeneous sensing infrastructures remains challenging because measurement consistency, sensor calibration, data fusion, and spatial reconstruction are often addressed separately rather than within a unified monitoring methodology. This work presents a hybrid environmental monitoring framework that integrates professional fixed monitoring stations with an autonomous ground vehicle equipped with low-cost environmental sensors. The proposed methodology combines reference-based calibration, temporal alignment, heterogeneous data fusion, and spatial interpolation to generate spatially consistent environmental information from complementary sensing platforms. The proposed methodology is experimentally validated through a monitoring campaign conducted within the IRCCS Policlinico San Martino hospital campus (Genoa, Italy), where repeated mobile measurements were integrated with two professional monitoring stations along a 350 m outdoor route characterized by heterogeneous environmental conditions. The calibration procedure significantly improved the agreement between fixed and mobile observations, while the comparative analysis of four interpolation techniques demonstrated that interpolation performance depends on the spatial distribution of measurements and the characteristics of the monitored environmental field rather than on the intrinsic superiority of a specific algorithm. The results further demonstrate the feasibility of integrating fixed and mobile sensing into a coherent and reproducible environmental monitoring workflow. Although validated in a hospital environment, the proposed methodology is applicable to other complex outdoor scenarios featuring distributed infrastructures and repeated operational routes, including industrial campuses, logistics hubs, freight terminals, airports, and port facilities.
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