This paper presents the design and implementation of iPONICS: an intelligent, low-cost IoT-based control and monitoring system for hydroponics greenhouses. The system is based on three types of sensor nodes. The main (master) node is responsible for controlling the pump, monitoring the quality of the water in the greenhouse and aggregating and transmitting the data from the slave nodes. Environment sensing slave nodes monitor the ambient conditions in the greenhouse and transmit the data to the main node. Security nodes monitor activity (movement in the area). The system monitors water quality and greenhouse temperature and humidity, ensuring that crops grow under optimal conditions according to hydroponics guidelines. Remote monitoring for the greenhouse keepers is facilitated by monitoring these parameters via connecting to a website. An innovative fuzzy inference engine determines the plant irrigation duration. The system is optimized for low power consumption in order to facilitate off-grid operation. Preliminary reliability analysis indicates that the system can tolerate various transient faults without requiring intervention.

The rapid growth of the Information and Communications Technology (ICT) sector requires additional infrastructure, such as more micro-datacenters and telecom stations, to support the higher internet speeds and low latency requirements of 5G networks. The increased power requirements of the new ICT technologies necessitate the proposal of new power supplies, in an attempt to support the increase in energy demand and running costs. This work provides an in-depth theoretical analysis on the losses of the individual stages of commercially available PSU and proposes a new multicell PSU, the buck PFC converter, which offers a higher overall efficiency at varying load levels. The theoretical results are verified using simulation results, via a PSIM Thermal Module, and using experimental data. The results indicate that multicell structures can improve the overall PSU efficiency by 1.2% at 50% rated power and more than 2.1% at full power. Finally, taking into consideration the economic implications of this study, it is shown that the proposed multicell structure may increase the PSU costs by 10.78%, but the payback period is in the order of just 3.3 years.

The enormous growth of telecom network technologies of this decade and the ever-growing data needs, will unavoidably increase the energy consumption of telecom base stations and datacenters. The energy demand increase tend to become a serious issue for both power grid operators and telecom network owners in the upcoming years. Having in mind that adding the 5G layer can consume more than double of a typical 3-cell system (consisting of 2G, 3G and 4G bands), the telecoms industry will need to find solutions to mitigate the increase in energy demand. In this work the energy/load profiles of different telecom stations are analyzed and correlated in discrete steps with the expected PV power generated profile taking into consideration the inherent presence of storage that telecom stations have. The work is validated through a technoeconomic feasibility study.

Power Supplies are a key part of the modern Internet and Communications Technologies (ICT) industry. Modern Uninterruptible Power Supply (UPS) systems are modular and as such, consists of several Power Supply Units (PSUs). Various PSU designs are used to optimize efficiency of operation at specific loading conditions, but this engenders inefficient operation at other loading conditions. To optimize the energy efficiency in various loading conditions, this paper proposes a novel power supply multiplexing system engaging different combinations of PSUs, controlled through machine learning techniques to maximize efficiency depending on the loading conditions. Each PSU combination is given a state number. Because of the vast number of combinations (States) that can occur in such systems and due to the redundancy requirements, that need to be met during multiplexing, machine learning techniques are adopted. It is shown that through the novel proposed system an efficiency improvement of over 78% can be achieved in low loading conditions, and an average 5.23% efficiency improvement in all loading conditions.

Datacenters are major components of the Information and Communication Technologies (ICT) responsible for storing, processing and transmitting enormous amounts of data every second. The significance and importance of datacenters in the world economy can be identified from studies which report that in 2023, datacenter infrastructures consumed a total of 4% of global electricity and contributed 3-5 % of global carbon emissions, whereas between the years of 2017-2021, datacenters added $2.1 trillion to the U.S. Gross Domestic Product (GDP). A big portion of energy supplied in datacenters is consumed by the required cooling systems hence companies do not favor developments in hot climate countries. However, due to environmental and climate change concerns along with the steep increase of energy production costs in recent years made the industry look for alternatives. This work includes an in-depth feasibility and comparative study of datacenter construction and operation in hot and cold European countries and addresses the environmental impact of photovoltaics integration in the electrical supply system. The study considers cost parameters (land, operating expenses, photovoltaic system, etc.), the net present cost and levelized cost of energy which are different for each European country under investigation. Furthermore, for every country under consideration, the PV generation was simulated using the PVsyst software which includes multiple meteorological databases, whereas the feasibility analysis was simulated using the HOMER Pro software which integrates components, resources and economic calculations. An elaborate analysis of the results knocks down the common belief that datacenters have lower operational and running expenses in cold climates because of lower cooling requirements. On the contrary, this study shows that hot climates with high solar radiation levels may favor the operation of datacenters by providing 45% higher green energy and 35% lower CO₂ emissions, whereas the cooling cost is only 5% higher. In addition, the break-even period for the photovoltaic system in Southern European countries with hot climates is 3-4 times faster.