SuSy Research is an independent research company. We do research and consultancy for - and with - other companies using models developed by our team.
Our focus is on “sustainable systems models”, that is, mathematical and engineering models to analyse and predict systems sustainability. These models can be applied in several markets, as health systems, economy networks, environment, power grids, business chain, transports, utilities, educational systems and so on.
Besides our tailor made research we have a few spin-off projects, showed below.
See our publications and get in touch for more information on how to push innovation forward.
SuSy Checker is the "building fitness app".
It analyses, with just one click on a map, the potential sustainability for any built environment in the world. SuSy Checker main focus is "the house". The home-user, for free, is empowered with our solutions and knowledge to improve energy efficiency, checking the building unique potential for solar and wind energy, water use, automation, as well as wellbeing by measuring local pollution, green areas and transports nearby.
SuSy Checker also helps vendors and service providers to meet end-user needs, commercial/industrial buildings to discover and improve their sustainability potentials, and governmental institutions to have a "big picture" of regional sustainability through our heat-maps on sustainability (see more).
COMSYSE is our initiative in Complex Adaptive Systems - CAS.
It is a platform to study, analyse and simulate complex systems. Our goal is to create solutions, based on CAS concepts and theory, for common problems in very different fields. COMSYSE keywords are: elements, interaction, adaptation, evolution, hierarchy, emergence.
Check the Comsyse website to explore these topics in depth (see more).
Innovation Emergence: Public Policies versus Actors’ Free Interaction
In this paper we argument that innovation flourishes and emerges in a creative environment where the actors interact freely, to the extent that this environment is a complex adaptive system. Public or institutional policies, trying to induce innovation, must be careful to not stifle or interrupt the emergence of novelties in the path from creation and conception to market involvement. Our proposed model argues that innovation emerges wherever evolution, learning, mutation, and competition between individuals and firms are permitted, without restrictions or pre-defined paths to the market.
(Systems 2018, 6(2). Full version here).
Dynamical Networks Modelling Applied to Low Voltage Lines with Nonlinear Filters
Network models consider static measurements, and here we develop an iterative model to deal with dynamical measurements. Our model uses reflected and incident signals, which are dependent on the node parameters, proceeding a time-step computation. Each node is a space representation that consolidates parameters for a specific vertex and its edges. Nonlinear functions are applied within the node and will contribute to the general process running on the structure. The idea of a structure and its related processes leads to a new concept of sustainability and system robustness.
(Applied System Innovation, 2020, 3(2). Full version here).
Complex systems: Risk model based on social network analysis
Risk is difficult to analyze and predict in complex systems, especially if it is necessary to assess mission-critical systems risks in real-time. This work proposes a theoretical model, based on social network analysis and risk classification. The aim is to understand risks from data and evidence obtained from the field, not coming from statistics of similar systems nor risk probabilities taken a priori. The analysis model seeks to design the structure or environment at risk as a complex system in which all components and relations are essential. It allows users to assess risks in real time.
( 2016 Int. Symposium on Industrial Electronics, IEEE-ISIE. Full version here).