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Artificial Neural Networks (ANNs) have been successfully applied to the problem of forecasting future load values, especially in the short term framework (a few minutes to a few hours ahead). Traditional analytical models have shown difficulties when dealing with (i) the highly variable demand curve shapes, (ii) some independent variables that exhibit random behaviour, and (iii) the identification of variables that could explain relevant load variations, such as weather variables. Current available ANN applications to this problem are by far aimed at a systemwide level, where the load behaviour is more regular than at substation or even primary feeder levels.

Purpose There is a great interest in developing eco-friendly operations as alternative uses of resources in the university campus, making the employment of technologies more sustainable. Practices such as energy management and efficiency initiatives have been encouraged to meet these sustainability goals. The purpose of this paper is to describe and discuss the main features of the GENIIOT project, a system of energy management using Internet of Things applied in a Brazilian university campus to support energy education practices and to promote lasting energy efficiency measures. The focus of the study is directed at the energy consumption of the air-conditioning system, which is responsible for 40% of the total electricity consumption. In addition, this project also scrutinizes processes such as the building occupants’ comfort demands, lighting levels and energy waste control. Design/methodology/approach A case study at the Unicamp campus was conducted to illustrate the design procedures through qualitative description. This study comprises an overview of the physical plant, hardware and software development, energy data monitoring, management process and energy education. Findings The GENIIOT project enables energy efficiency actions by concerning the use of air-conditioning equipment based on monitored data, different types of monitored rooms, user’s behaviors and their feedback. This initiative requires the engagement, awareness and actions from users combined with investment in energy efficiency to achieve an efficient use of this type of equipment. The proposed approach can be applied in the future to similar situations, inside the Unicamp campus and at other university campuses. In addition, this project can contribute to building efficiency analysis by using the hardware structure developed to monitor facilities and carry out evaluations, providing valuable information for strategic initiatives in energy efficiency projects and research and development programs based on practical experience and promoting a discussion about sustainability aspects in the context of the university campus for energy efficiency. Originality/value The GENIIOT project is aligned with some of the sustainable development goals, among which sustainability and responsible consumption are identified. Considering the sustainability issues, the economic dimension can be evaluated through a cost–benefit analysis of energy efficiency projects with prudent investment, while the social attractiveness of the project is ensured by education and awareness practices for the community that interacts with the system and learns about a more efficient way of using resources in the campus. Furthermore, there is a more conscious use of natural resources by minimizing waste from the use of electricity and reducing carbon dioxide emissions. GENIIOT is part of Sustainable Campus Project, a living laboratory which aims at developing energy-efficiency-related research activities in the university campus to reduce costs in higher and federal institutions of education in Brazil.