Automated uninterruptible power supply battery protector: case study of Tanzania atomic energy commission, Arusha-Tanzania

A Project Report Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Science in Embedded and Mobile Systems of the Nelson Mandela African Institution of Science and TechnologyUninterruptible Power Supply (UPS) is electrical apparatus that provides emergency power to its load when the input power source fails and manages power fluctuations through its battery during power failure to allow a user to save work and shut down a system procedurally. The UPS’ electrical ability depends on its battery’s strength. At Tanzania Atomic Energy Commission (TAEC) users mostly leave their UPS on as they go home, and when there is blackout, the UPS batteries get drained to zero leading to a significant number of UPS getting damaged in a year. Automated Uninterruptible Power Supply Battery Protector (AUPSBP) is developed to protect UPS battery at the institution using Kanban Agile methodology which supported teamwork. The AUPSBP monitors the voltage from mains to UPS using a voltage sensor. When the sensor detects a lack of voltage from the mains to UPS, AUPSBP triggers timer counting down towards switching the UPS off. When tested, AUPSBP switched off the UPS when the set time of 5 minutes elapsed, and when UPS battery voltage was <100V protecting UPS battery from draining to zero during blackout. It sent Short Messages using Global System for Mobile communication when mains power was switched off, and when UPS was switched off before the set time of 5 minutes elapsed. The AUPSBP is effective for switching off UPS before its battery drains to zero to prevent battery damage on different types and sizes of UPSs with only changes in switch and timer. Therefore, AUPSBP is needed to protect UPS at TAEC

Security in Computer and Information Sciences

This open access book constitutes the thoroughly refereed proceedings of the Second International Symposium on Computer and Information Sciences, EuroCybersec 2021, held in Nice, France, in October 2021. The 9 papers presented together with 1 invited paper were carefully reviewed and selected from 21 submissions. The papers focus on topics of security of distributed interconnected systems, software systems, Internet of Things, health informatics systems, energy systems, digital cities, digital economy, mobile networks, and the underlying physical and network infrastructures. This is an open access book

A forecast of the Cloud

IT ses ofta som en del av lösningen för att uppnå ett hållbart samhälle genom till exempel minskat resande, optimering av industri- och jordbruksprocesser, intelligenta elmätare och smarta hem. Något man sällan reflekterar över är att ITbranschen själv också bidrar till elanvändningen. Ett nytt fenomen inom IT-världen är molnet som ger möjlighet till som det verkar outtömliga resurser i form av lagrings- och beräkningskapacitet, konstant uppkoppling och snabb överföring. Det finns många definitioner av molnet men om man ser på det materiellt består det av datahallar i olika storlek samt fasta och trådlösa nätverk som drar el dygnet runt. Om användningen av molntjänster ökar – hur mycket kommer elanvändningen öka och med den också den globala uppvärmningen? I denna studie kommer molnet definieras, materialiseras och kvantifieras för att kunna bedöma dess elbehov idag och i framtiden. Lagar och regler för energieffektivisering kommer undersökas och framtida prognoser tas fram genom tillväxtmodeller. De huvudsakliga resultaten är: - Det finns inga lagar för hur energieffektiva datahallar måste vara, även om det görs en del inom området på frivillig basis och företag tar på sig egna miljömål. Europeiska unionen inkluderade vissa delar av servrar i ekodesigndirektivet år 2014 vilket visar på att problemet har börjat tas upp. - Användningen av molnet kommer öka explosionsartat i framtiden och det finns stor potential för energieffektivisering när det gäller lagring, bearbetning och överföring av data. Beroende på hur mycket som energieffektiviseras kan molnet komma att konsumera mellan 5 000 och 10 000 TWh år 2040. Detta kan jämföras med hela IT-branschen som 2010 drog mellan 700 och 1 000 TWh. Om man jämför molnet och traditionell IT är molnet oftast mer energieffektivt bland annat därför att resurser förbrukas efter behov och servrar utnyttjas optimalt. Det finns alltså ännu större potential för energieffektivisering om hela IT-sektorn inkluderas. - Om inte energieffektivisering sker alls kommer molnets energiförbrukning öka bortom greppbara magnituder. Det finns dock också studier som pekar på att den totala energikonsumtionen kan minska sett från idag, även om användningen av molnet ökar, då teknik med mycket bättre energiprestanda håller på att utvecklas. - Då dagens lagstiftning inte täcker in energieffektivisering ligger ett stort ansvar på företag att göra detta på frivillig basis, vilket till viss del motiveras av att de sparar pengar genom att energieffektivisera. Det är dock mycket viktigt att denna energiåtgång uppmärksammas och att den inte tillåts skena iväg i framtiden.Information and communication technology (ICT) is often seen as part of the solution for a sustainable society, for example through reduced travel, optimization of industrial and agricultural processes, smart meters and smart homes. However, something usually left unconsidered is the electricity consumption of ICT itself. A new phenomenon of the ICT industry is the Cloud that enables seemingly inexhaustible resources in terms of storage and computing capacity, constant connection and fast transfer. There are many definitions of cloud but if looked at from a material point of view it consists of data centers in different sizes as well as wired and wireless networks that consumes electricity. If usage of cloud services increase - how much will electricity consumption and with it global warming increase? In this study the cloud is defined, materialized and quantified in order to estimate its electricity demand today and in the future. Laws and regulations for energy efficiency will be examined and future forecasts are created with the use of growth models. The main results are: - There are no regulations of how energy efficient data centers must be, even though some companies set their own environmental goals and voluntary projects are carried out. The European Union included some parts of servers in the Ecodesign Directive in 2014, which shows that the problem has begun to be addressed. - The usage of the cloud will increase dramatically in the future and there is great potential to improve energy efficiency in terms of storage, processing and transmission of data. Depending on how energy efficient the cloud will be it can consume between 5 000 and 10 000 TWh in 2040. This can be compared to the entire ICT industry which consumed between 700 and 1 000 TWh in 2010. If the cloud is compared with traditional IT it is usually more energy efficient as resources are pooled and used when needed and servers are utilized optimally. Therefore there is even greater potential for improving energy efficiency if the entire ICT sector is included. - If there are no energy efficiency improvements at all the cloud’s energy consumption will increase beyond graspable magnitudes. However, there are also studies that indicate that the total energy consumption can decrease in the future, even though the use of the cloud increases, due to new efficient technologies currently under development. - As current regulations do not include energy efficiency of data centers, a huge responsibility is placed at companies to do this on a voluntary basis. The companies do however have a self-interest to improve energy efficiency as it saves them money - but is it enough? It is very important that this energy consumption is recognized and is not allowed to increase out of control in the future.Den ökande användningen av onlinetjänster medför att elkonsumtionen från datahallar och nätverk kommer skjuta i höjden om vi inte energieffektiviserar. Idag saknas det generellt lagar om hur effektiva datacenter måste vara. Ett enormt ansvar läggs på att företag själva är förutseende och satsar på energieffektiv teknik. Det finns dock stora möjligheter att spara energi, både för datahallar och nätverk - om viljan finns

A smart environmental monitoring system for data centres using IOT and machine learning

A Project Report Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Science in Embedded and Mobile Systems of the Nelson Mandela African Institution of Science and TechnologyData centres are a crucial part of many organizations in the world today consisting of expensive assets that store and process critical business data as well as applications responsible for their daily operations. Unconducive environmental conditions can lead to decline in performance, sporadic failures and total damage of equipment in the data centers which can consequently lead to data loss as well as disruption of the continuity of business operations. The objective of this project was to develop an environmental monitoring system that employs Internet of Things (IoT) and machine learning to monitor and predict important environmental parameters within a data centre setting. The system comprises of a Wireless Sensor Network (WSN) of four (4) sensor nodes and a sink node. The sensor nodes measure environmental parameters of temperature, humidity, smoke, water, voltage and current. The readings captured from the sensor nodes are sent wirelessly to a database on a Raspberry Pi 4 for local storage as well as the ThingSpeak platform for cloud data logging and real-time visualization. An audio alarm is triggered, and email, Short Message Service (SMS), as well as WhatsApp alert notifications are sent to the data centre administrators in case any undesirable environmental condition is detected. Time series forecasting machine learning models were developed to predict future temperature and humidity trends. The models were trained using Facebook Prophet, Auto Regressive Integrated Moving Average (ARIMA) and Exponential Smoothing (ES) algorithms. Facebook Prophet manifested the best performance with a Mean Absolute Percentage Error (MAPE) of 5.77% and 8.98% for the temperature and humidity models respectively. In conclusion, the developed environmental monitoring system for data centers surpasses existing alternatives by integrating forecasting capabilities, monitoring several critical parameters, and offering scalability for improved efficiency and reliability. The study recommendations include exploring a Web of Things (WoT) approach and incorporating instant corrective measures for improved performance

Integrated scalable system for smart energy management

The planet's reserves are encountering vital challenges and suffer inequitable consumption. The outcomes of the prostration of natural reserves have started affecting every single organism on the globe. Energy is a critical key factor in this aspect because a considerable part of the destruction is triggered by utilising the planet reserves to produce power in diverse forms. The increasing environmental awareness in humans' minds, and the rapid development of smart concepts, home automation technologies in both hardware and software fields, played an essential role in speeding up the progress to apply smart energy management which is needed to revert the situation to its appropriate track by focusing on two main divisions: firstly, producing clean and renewable energy and secondly, reducing the loss of the total generated energy. This research will concentrate on the second approach by proposing, implementing and evaluating a contemporary integrated, scalable, smart energy management framework that assists in reducing the energy consumption in the household sector, covering a range of single households till huge communities and big organisations with thousands of appliances. A number of correspondent strategies and policies which utilise a set of observed and predicted system entities are applied to keep meetings the most relevant quality attributes such as integrability, scalability, interoperability and availability. IoT concepts are applied in this context to connect conventional household appliances to a farm of microservices that implement predictive analytics techniques to reduce energy consumption by applying two main strategies; appliance substitution based on the energy consumption and creating automatic schedules to run appliances based on predictions. A case study is presented on two sample appliances within the household to illustrate the framework validity and deliver percentage figures of the saved energy. Additionally, the framework offers a number of possibilities to provide relevant third parties such as local energy providers, apparatuses' manufacturers, or pertinent government offices with various appliances’ operational behaviours under real-life conditions

Radio frequency energy harvesting for autonomous systems

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyRadio Frequency Energy Harvesting (RFEH) is a technology which enables wireless power delivery to multiple devices from a single energy source. The main components of this technology are the antenna and the rectifying circuitry that converts the RF signal into DC power. The devices which are using Radio Frequency (RF) power may be integrated into Wireless Sensor Networks (WSN), Radio Frequency Identification (RFID), biomedical implants, Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), smart meters, telemetry systems and may even be used to charge mobile phones. Aside from autonomous systems such as WSNs and RFID, the multi-billion portable electronics market – from GSM phones to MP3 players – would be an attractive application for RF energy harvesting if the power requirements are met. To investigate the potential for ambient RFEH, several RF site surveys were conducted around London. Using the results from these surveys, various harvesters were designed and tested for different frequency bands from the RF sources with the highest power density within the Medium Wave (MW), ultra- and super-high (UHF and SHF) frequency spectrum. Prototypes were fabricated and tested for each of the bands and proved that a large urban area around Brookmans park radio centre is suitable location for harvesting ambient RF energy. Although the RFEH offers very good efficiency performance, if a single antenna is considered, the maximum power delivered is generally not enough to power all the elements of an autonomous system. In this thesis we present techniques for optimising the power efficiency of the RFEH device under demanding conditions such as ultra-low power densities, arbitrary polarisation and diverse load impedances. Subsequently, an energy harvesting ferrite rod rectenna is designed to power up a wireless sensor and its transmitter, generating dedicated Medium Wave (MW) signals in an indoor environment. Harvested power management, application scenarios and practical results are also presented

Design And Evaluation Of Wireless Technology Systems For Data Analysis

DissertationThe internet and cloud storage are becoming increasingly important to researchers, hobbyists and commercial developers. This includes the transmission of reliable data as the availability and functionality of remote sensors and IoT devices are becoming more common. The availability of high-speed internet connections, like fibre-optic cable, LTE and digital radios, changed the playing field and enabled the user to transmit data to cloud storage as speedily as possible. With these various technologies available, the question now arises: Which technology is more reliable and efficient for IoT sensors and for users to transmit data to a cloud server? This project aims to investigate the reliability and transmission delay of transmitted data from Wi-Fi, GPRS Class 10, and digital radio networks to cloud storage. A sampling unit was designed to evaluate analogue inputs periodically and send the recorded data to the three technologies under test. It also records the data to an on-board micro SD card along with an indexing system. The systems then transmit the sampled data and index number to a cloud storage server via the communication technologies under test. The cloud-stored data is then compared with the recorded data of the sampler unit to determine data integrity. The transmission delays can be calculated by using the cloud storage server’s time stamp information and the original time stamp of each data message. From the results acquired in the research, it showed that digital radio is a very reliable and stable means of data communication but it lacks direct connection to the internet. Although, both Wi-Fi and GPRS Class 10 are permanently connected to the internet, it was also observed that Wi-Fi internet connectivity may be susceptible to interference from external factors like the continuity of supply from the national power grid and from load shedding. It also showed that the XBee digital radio system lost 0.21% packets compared to the 0.31% for Wi-Fi and 1.46% for GPRS Class 10. On the other hand, although GPRS Class 10 may be a bit less reliable than digital radio and Wi-Fi, it is relatively cheap to use and has the ability to connect to multiple communication towers for communications redundancy. The outcome of this research may help researchers, hobbyists and commercial developers to make a better-informed decision about the technology they wish to use for their particular project

Design, analysis and control of solar heating system with seasonal thermal energy storage

The majority of the electricity consumption in Canadian single-family house is for space heating and water heating. Currently, around 99% house in Canada using the conventional grid electricity for those purposes. To utilize the sun’s free energy for space heating and domestic water heating, first a sessional solar thermal energy storage system (SSTES) has been designed and investigated to determine their thermal and electrical performance of a house consists of four persons in the Canadian climate environment. The detailed mathematical formulation and sizing of each SSTES system component have been developed. Similarly, the components mathematical modelling, sizing of solar collector-based TES system, a hybrid solar Photovoltaic thermal (PV/T) based TES system, a Photovoltaic based TES system has been designed. To validate the feasibility and numerical studies of the developed STES configurations, all configurations have been simulated in a professional thermal simulation software named as PolySun, and only solar collector-based TES system has been designed and simulated at MATLAB/Simulink environment packages. The proposed TES system performance have been compared with the existing conventional system. All configurations have been tested using the solar radiation and other weather data of St. John’s city/NL city in Canada. The main objective to design a suitable TES system for space heating and water heating so that the residence can save high monthly electricity bill. For experimental validation, an open source IoT platform named openHAB smart home automation is used as a home server, an ESP32 Thing microcontroller board has been used as Microcontroller unit where all sensors and output devices (relays, thermostat settings channels) are connected for data acquisition and control. The proposed setup is able to monitor the TES system parameters, and able to control locally/remotely and manually/automatically. The proposed system is the low cost, low power consumption prototype which will be a commercial solution of TES system monitoring and remote control