Climate change and global warming are the greatest harmful consequences of human activity. Indeed, Human technological development and demographic growth has been accompanied by globalization. In this new era, the logistics revolution has removed borders and industrial value chains have been distributed all over the world. It is becoming difficult to attribute responsibilities for ecological impacts accurately, since consumers are not necessarily in the same area as the countries of manufacture or extraction of raw materials. At the same time, a new paradigm called the Internet of Things has come to reshape our relationship to the world. The smallest everyday objects are connected to the Internet and allow acquisition of large amount of data, interact with cyberspace and in some cases act on the real world in an automated way. On the other hand, the last decade has also seen the rise of a new technology for storing transactions data in a reliable and consented way. Blockchain has changed the way operations are made based on the concept of distributed ledger giving a new breath to the economy. They have also dived into companies business by allowing private implementations with permissioned blockhains. The aim of this work is to take advantage of the power of the two technologies combined -the Internet of Things provides GIEFC wide possibilities when it comes to collecting information and establishing controls on the one hand, and blockchain provides very good means to ensure traceability while respecting confidentiality and privacy -in order to create a global architecture for a digital ecological impact calculator respecting privacy. In order to validate our proposal we first modeled it with a Petri network in order to verify its functioning, then we implemented it in order to measure average running time of each major step: for operations relative to certification authority we have obtained 0.342 second per operation, 0.342 second per operation concerning production and buying actions reporting and 0.299 second par scoring operation. Finally we used these outputs to build a queue model in order to check if the proposed architecture steady-state does not change over time. As results we showed that for the simplest form of queue model the servers of our architecture have a utilization rate that is close to 50% and that the overall waiting time remains below one minute, on the other hand with the Petri net we have proved from the marking graph that GIEFC performs the expected tasks according to the described specifications.