Building Advanced Metering Infrastructure using Elasticsearch Database and IEC 6205621 Protocol Building automation systems have been already around for many years. Unfortunately, the still high cost of smart building installation is difficult to justify for many noncommercial applications such as residential buildings and houses. The ongoing IoT revolution and popularization of lowcost ubiquitous networking changes drastically the situation. Nowadays, using offtheshelf hardware and cloud based computing, it is easier to provide to the end user the intelligent solution which can be easily deployed and do not require significant building refurbishment. Even partial implementation of smart building concept will result in increase of energy efficiency as well as comfort of building occupants. In this paper, the solution for controlling and monitoring energy consumption in medium size rent building (12 flats) is presented. The idea of the project was to use readymade, commercially available hardware and extend its functionalities with custom software. In addition, the Elasticsearch database was used to store energy usage data.

Open IoT Infrastructures for InHome Energy Management and Control This paper presents an IoTbased infrastructure that uses currently available technologies for the implementation of a complete energy management system (EMS). This solution aims to reduce the cost of energy and ease the integration of distributed energy resources (DERs) and energy storage systems (ESSs) at a consumer level. It integrates IoTready power converters, for DERs and ESSs, smart meters, smart sensors and actuators. A FIWARE IoT Platform has been used for the integration of different physical devices, data management, energy management algorithms, and data visualization. The full system has been implemented at IoT Microgrid Laboratory at Aalborg University. The proposed infrastructure presents numerous advantages such as providing more information to the EMS, which enables direct control of generation, energy storage, and consumption, as well as a seamless integration in any previous infrastructure as it uses wireless technologies. This also unlocks the implementation of complex algorithms that involve both generation and demandside management, limited in a conventional EMS, due to the lack of data or actuation capabilities. Preliminary results are shown in this paper proving the operation of the EMS and the infrastructure.