# IoT Middleware Platforms for Smart Energy Systems: An Empirical Expert Survey
## 1 Introduction  
The Internet of Things (IoT) is understood as a ubiquitous, complex network of networkable, heterogeneous entities or \"things\" [1]. It collects environmental data; interacts with the physical world; communicates through internet standards; and provides applications, data transfer and data analysis [2] with minimal human interaction [3]. Developments in web and communication technology and the wide availability of microchips have accelerated the integration of computing machinery into all aspects of day-to-day life.  
The application of IoT technology to the urban and building sector provides opportunities, especially within the context of sustainability [4; 5]. Socioeconomic changes, such as the trend towards larger homes, the automation of household chores and the advent of energy-consuming entertainment devices, have caused the buildings sector to become the largest contributor to global energy demand [6], accounting for 40% of the energy consumption in the European Union (EU) [7] and 78% of greenhouse gas emissions in the EU and Iceland [8]. The integration of renewable energy technologies into the existing energy systems and the resulting decentralization and introduction of environmentally-friendlyenergy technologies are promising use cases for IoT. Services such as monitoring, maintenance and predictive control can be used to manage distributed generation and storage technologies [9] and improve operational efficiency and reliability in the energy supply system [10]. The broad availability of operational sensor data stimulates the development of data-driven services, such as energy forecasting [11], automatic fault detection [12], demand-side management and predictive control [13]. Real-time data collection allows municipal, district and building operators to streamline monitoring and maintenance through automation. In the literature, there are many works describing the application of these technologies in practice [14; 15; 16; 17; 18; 19].  
Communication between networkable, heterogeneous computational components, i.e., machine to machine (M2M) communication, is a key requirement in any cyber system. However, state-of-the-art devices from different vendors often employ incompatible protocols and data formats, which inhibits interoperability. There are two approaches to mitigate this issue: (i) the introduction of universal standards and (ii) the use of translation layers, so-called middleware platforms, between the components. The introduction and even more importantly, the enforcement of standards, has proven non-trivial in many instances. Consider, for example, electric socket types in Europe, or controversies around different charger standards for small electronic devices [3]. Besides, the cost of retrofitting existing systems with components that adhere to novel universal standards can be prohibitive, so backward-compatibly has to be considered as well. Consequently, practitioners typically use middleware solutions in their IoT systems.  
Due to the diverse set of requirements and applications, IoT platforms need to cover a wide range of functionalities, non-functional requirements and scales [20]. To match the growing demand, there exists a considerable number of commercial and non-commercial IoT solutions. However, only a few commercial competitors include the energy sector in their portfolios. Possible reasons include the severity of security risks in what is considered to be critical infrastructure and a lack of global, universal standards [3; 14; 21].