ARIES Innosuisse Project

Exploiting User Journeys and Testing Automation for Supporting Efficient Energy Service Platforms


ZHAW Zurich University of Applied Sciences


ARIES project delivers a user-oriented self-adaptive software platform that implements requirements and testing engineering mechanisms to enhance customer experience. ARIES project is realized in the context of LEDCity, a Swiss start-up specialized in AI-based optimization of lighting systems, in collaboration with ZHAW.


WE BELIEVE in DevOps Innovations

Emerging Efficient Energy Service Platforms (EESP) are pushing the boundaries of DevOps practices and processes, with new challenges to handle for both practitioners and researchers. LEDCity (start-up in Switzerland) and ZHAW employ DevOps innovations to sustain the evolution of future EESP services reliability, evolvability, and testability.

Our Objectives

LEDCity is a Zurich based cleantech start-up and develops an autonomous plug and play lighting system to reduce the energy consumption of lighting by 90% compared to conventional lights. LEDCity’s AI-based optimization of lighting systems (OLS) is a radical new approach to sensor controlled lighting systems. OLS can reduce the energy consumption of lighting through automation. They have a highly effective AI-trained plug and play LED lighting system which is smart, simple and efficient. In each light there are sensors which can adjust light quickly and smoothly. The control unit is decentralized, so there is no need for an expensive management system. This brings challenges to the DevOps process, in both development and testing phases. The ARIES project aims at enhancing LEDCity’s DevOps pipeline, the quality of LEDCity's services, and its customers' experience, by implementing four main components.

A self-adaptive and real-time analyzer

Enabling data diagnosis from the operational data of the sensors from the system (e.g., “day-light measurements”, “level of humidity”)

A self-adaptive component performing change analysis.

The focus is to support complexity and risk monitoring in the development process and providing outputs for test engineering

A self-adaptive component

Gathering requirements for enabling testing engineering, generation, automation LEDCity mechanisms and supporting regression testing automation

A component integrating feedback loop mechanisms

To assess the correctness of real-time measurements (e.g., day-light measurements estimators)