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Autonomic edge computing for air quality monitoring

  • PROJECT TITLE: Autonomic edge computing for air quality monitoring
  • PROJECT LEADER: Michael Mrissa, PhD
  • PERIOD: 01.09.2020 – 31.08.2023
  • BUDGET: €299,954.88 (€184,703.76 for InnoRenew CoE)
  • FINANCING: Slovenian Research Agency (ARRS)
  • PROJECT COORDINATOR: InnoRenew CoE (Slovenia)
  • PARTNERS: UP FAMNIT (Slovenia); Institute for the Protection of Cultural Heritage of Slovenia (Slovenia)

Reducing the environmental, material and energy impacts of buildings is a major priority of the European Union [1] and is highlighted in the United Nation’s Sustainable Development Goals [2].

Buildings equipped with intelligent sensor systems (smart buildings), which can report the performance status of their elements to help optimize energy consumption and maintenance as well as inform future building design, are an important part of reaching this goal. Equipping buildings with wireless sensor networks (WSNs) is particularly helpful in contributing to this goal as well as improving the well-being of building users.

Typical approaches make use of cloud facilities for data upload and remote processing to manage buildings along their life cycle (conception, construction, use and end of life). Typical approaches present several drawbacks, however: dependency on cloud service providers, heavy network use, poor performance (network latency), privacy concerns due to remote computation and unsuitable data sharing strategies.

More recently, we have witnessed a drastic evolution of embedded devices that include more and more sensors, thus driving researchers to reconsider the typical cloud-based approach and distribute data and processes (back) to the network – a concept called edge (or fog) computing. Edge computing provides optimized network usage, dynamic network configuration and data management; it also enables distributed on-site data processing, low latency response to network changes and independence from cloud providers.

In this project, we will explore edge computing solutions that take advantage of a new generation of WSN devices, reducing the global environmental cost of such equipment.

InnoRenew CoE project activities

InnoRenew CoE, as a project leader, will investigate ways to merge theoretical tools (graph and infection models), technologies (semantic web services, distributed ledger technology) and distributed data mining that may help design and implement dynamic self-configuring networks. We will demonstrate our work with four pilots in Slovenia and abroad.