Climate change mitigation and adaptation tasks become well integrated in national and municipality strategies. A noteworthy example that has sparked debate in Finland is the draft of the EU Energy Efficiency Directive (European Commission, 2021; 2023a; 2023b), presenting new demands that property owners will likely face in the future. According to the recent assessments, the directive aims to improve energy efficiency by 32.5% by 2030 and reduce CO2 emissions by 55% by the same year. These requirements can potentially affect at least 40% of Finland’s building stock and cumulatively create yearly demand for materials, solutions and services amounting to 1-1.5 bn euros (RAKLI ry 2023).
Rodionova (2023) dedicated her Master’s thesis in information technology to the cause of advancing the objectives of the EU Energy Efficiency Directive. The topic of the thesis is the integrated development of scalable ML-enhanced dataflows from single pipeline applications towards mature data platforms. The work concentrates on optimization of energy renovation costs facing building owners.
Building physics assessments play an important role in the extensive scope of works related to planning of energy renovations and adaptation to climate change. Changes in climate conditions expose building facades to novel stresses (Vinha et al. 2013). Sensor monitoring can detect the possibility of structural damage before it significantly affects the buildings, while ML-enriched scenario algorithms prevent over-dimensioning of structural solutions, in both cases saving building materials. Scaling these workflows to Big Data and cities’ data infrastructures creates powerful decision-making tools.
However, responsible integration of IoT into urban decision-making requires both novel methodologies (Lee et al. 2022), risk management expertise (Rodionova & Oldenburg 2023) and dedication to inclusive physical and digital urban spaces (Mattern 2021). IoT networks’ growing capacity requirements (Lea et al. 2020) should be balanced with sustainable development limitations. Scenario work necessitates closer collaboration among different experts and stakeholders and incorporating long-term risk management into business reporting (Arias et al. 2022). Digital twins’ analytical capacities can become instrumental in connecting buildings component data to insights related to occupants’ comfort, perceived security of the neighbourhoods, and economic parameters such as rental income.
The McKinsey Global Institute estimates that by 2025, a potential economic impact of IoT applications, primarily linked to B2B services, will reach up to 11 trillion euros (Remotti 2021). The sustainable development potential of such applications heavily relies on viable governmental and municipal policies. Apart from fostering the emergence of innovative IoT technology clusters, such policies should also employ service-based logic to guide technology development towards multi-faceted, pro-social, and pro-environmental objectives.
Authors
PhD candidate, MSt Katja Rodionova graduated from the Master’s programme “From IoT to AI” in Information and Communications Technology at LAB University of Applied Sciences in 2023.
Minna Asplund is a senior lecturer in Information and Communications Technology and the coordinator of the Master’s programme “From IoT to AI” at LAB University of Applied Sciences.
References
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