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Energy has become the most expensive and critical resource for all kinds of human activities. At the same time, all areas of our lives strongly depend on Information and Communication Technologies (ICT). It is not surprising that energy efficiency has become an issue in developing and running ICT systems. This paper presents a survey of the optimization models developed in order to reduce energy consumption by ICT systems. Two main approaches are presented, showing the trade-off between energy consumption and quality of service (QoS).

In this paper the idea of functioning of Building Management Systems and Object Management Systems in intelligent buildings is presented. New functionalities of intelligent buildings resulting from the introduction of microgeneration are described. Low-Power Wide-Area Networks (LPWAN) are characterized and compared. The selected Long-Range (LoRaWAN) technology is tested for its use for communication with energy meters and monitoring the power supply network in intelligent buildings. In the paper a new system for reading and monitoring the network is proposed, consisting of hardware, communication, and application layers. A key element of the system is a specially developed converter, which has been designed and tested in a real urban environment. Using our solution in practice could allow to change the architecture of a measurement data acquisition system to much more flexible and efficient.

In this paper, the potential to reduce the energy consumption of end devices operating in a LoRaWAN (long-range wide-area network) is studied. An increasing number of IoT components communicating over wireless networks are powered by external sources. Designers of communication systems are concerned with extending the operating time of IoT, hence the need to look for effective methods to reduce power consumption. This article proposes two algorithms to reduce the energy consumption of end devices. The first algorithm is based on the use of a measured value prediction, and the second algorithm optimizes the antenna gain of the end device. Both algorithms have been implemented and tested. The test experiments for reducing energy consumption were conducted independently for the cases with the first algorithm and then for the second algorithm. The possibilities of reducing energy consumption were also investigated for the case when both algorithms work together. The proposed predictive algorithm reduced energy consumption the least. Better results in reducing energy consumption were guaranteed by the algorithm optimizing antenna power. The greatest gain was achieved using both algorithms simultaneously. Tests of the developed algorithms, in laboratory conditions and in conditions with a change in the distance between the end device and the LoRa gateway, confirmed the possibility of reducing energy consumption during the transmission of measurement data in a low-energy wireless LoRaWAN. Reducing electric energy consumption by even a few percent for a single device can result in significant savings on a global scale.