Progress
Since the project’s initiation, Sigma-IoT has successfully completed its first implementation milestone. Key achievements include:
- Installation of advanced energy metering devices (Shelly Pro EM-50) and seamless integration with the existing NFC-based access control system across multiple office zones in Thessaloniki, Greece.
- Establishment of real-time data ingestion pipelines and backend infrastructure utilizing TimescaleDB, eliminating the need for local gateways.
- Daily integration of meteorological data via the Open-Meteo API to enhance context-aware energy optimization, particularly for HVAC and lighting systems.
- Preliminary development of AI-based models for energy demand forecasting and anomaly detection, trained on live data from six distinct pilot zones.
- Design and prototyping of a mobile application interface offering real-time dashboards, occupancy analytics, and personalized sustainability recommendations.
- Execution of the first stakeholder engagement workshop to ensure alignment between technical implementation and user expectations.
The project is now transitioning to the advanced analytics phase, which will focus on the development and validation of the intelligence layer, including explainable AI-driven decision support tools.
Expected results
Upon completion, the Sigma-IoT project will deliver an integrated, intelligent platform designed to optimize energy management within office environments, combining technological innovation with measurable sustainability outcomes.
Development of a Smart Energy Management Platform
The core outcome of the project will be a fully operational platform that consolidates real-time data from IoT energy meters, occupancy detection systems, and environmental sources. This infrastructure will support dynamic monitoring and decision-making processes to enhance energy efficiency, reduce consumption, and improve overall operational performance.
Implementation of Advanced Artificial Intelligence Models
The project will deploy a suite of AI-driven models capable of:
- Forecasting energy demand and occupancy levels using time-series and machine learning techniques
- Identifying anomalies in energy consumption that may indicate inefficiencies or malfunctions
- Generating context-aware recommendations using fine-tuned large language models (LLMs), offering intuitive and actionable insights to building managers
These capabilities aim to facilitate data-informed decision-making and enable predictive, rather than reactive, energy management.
Deployment of a Dedicated Mobile Application
An Android-based mobile application will be developed to provide end-users with access to:
- Real-time and historical data visualizations
- Occupancy and weather overlays
- Personalized energy-saving recommendations and alerts
The application will enhance user engagement and empower building staff to contribute to energy-saving efforts in their daily routines.
Provision of Open-Source Technical Resources
To encourage replication and future adoption, Sigma-IoT will release key components of the system under open-source licensing, including:
- Standardized data schemas
- RESTful API documentation
- UI/UX templates for mobile and web interfaces
These assets will support developers, municipalities, and enterprises seeking to implement similar solutions in diverse operational contexts.
Validated Energy and Environmental Impact
All system components and functionalities will undergo real-world validation, supported by quantitative metrics that demonstrate reductions in energy consumption, operational costs, and environmental footprint, alongside improvements in thermal comfort and space utilization.
Development of Replication Guidelines
Comprehensive deployment playbooks will be produced to facilitate the transferability of Sigma-IoT to other office buildings, public facilities, and smart infrastructure projects across Europe. These guides will include technical specifications, integration procedures, and recommendations for stakeholder engagement.