Element speciation and behaviour in metal-rich Boreal river and estuarine systems using ultrafiltration and chemical modelling

The bioavailability of metals and their potential for environmental pollution depends not simply on total concentrations, but is to a great extent determined by their chemical form. Consequently, knowledge of aqueous metal species is essential in investigating potential metal toxicity and mobility. The overall aim of this thesis is, thus, to determine the species of major and trace elements and the size distribution among the different forms (e.g. ions, molecules and mineral particles) in selected metal-enriched Boreal river and estuarine systems by utilising filtration techniques and geochemical modelling. On the basis of the spatial physicochemical patterns found, the fractionation and complexation processes of elements (mainly related to input of humic matter and pH-change) were examined. Dissolved (<1 kDa), colloidal (1 kDa-0.45 μm) and particulate (>0.45 μm) size fractions of sulfate, organic carbon (OC) and 44 metals/metalloids were investigated in the extremely acidic Vörå River system and its estuary in W Finland, and in four river systems in SW Finland (Sirppujoki, Laajoki, Mynäjoki and Paimionjoki), largely affected by soil erosion and acid sulfate (AS) soils. In addition, geochemical modelling was used to predict the formation of free ions and complexes in these investigated waters. One of the most important findings of this study is that the very large amounts of metals known to be released from AS soils (including Al, Ca, Cd, Co, Cu, Mg, Mn, Na, Ni, Si, U and the lanthanoids) occur and can prevail mainly in toxic forms throughout acidic river systems; as free ions and/or sulfate-complexes. This has serious effects on the biota and especially dissolved Al is expected to have acute effects on fish and other organisms, but also other potentially toxic dissolved elements (e.g. Cd, Cu, Mn and Ni) can have fatal effects on the biota in these environments. In upstream areas that are generally relatively forested (higher pH and contents of OC) fewer bioavailable elements (including Al, Cu, Ni and U) may be found due to complexation with the more abundantly occurring colloidal OC. In the rivers in SW Finland total metal concentrations were relatively high, but most of the elements occurred largely in a colloidal or particulate form and even elements expected to be very soluble (Ca, K, Mg, Na and Sr) occurred to a large extent in colloidal form. According to geochemical modelling, these patterns may only to a limited extent be explained by in-stream metal complexation/adsorption. Instead there were strong indications that the high metal concentrations and dominant solid fractions were largely caused by erosion of metal bearing phyllosilicates. A strong influence of AS soils, known to exist in the catchment, could be clearly distinguished in the Sirppujoki River as it had very high concentrations of a metal sequence typical of AS soils in a dissolved form (Ba, Br, Ca, Cd, Co, K, Mg, Mn, Na, Ni, Rb and Sr). In the Paimionjoki River, metal concentrations (including Ba, Cs, Fe, Hf, Pb, Rb, Si, Th, Ti, Tl and V; not typical of AS soils in the area) were high, but it was found that the main cause of this was erosion of metal bearing phyllosilicates and thus these metals occurred dominantly in less toxic colloidal and particulate fractions. In the two nearby rivers (Laajoki and Mynäjoki) there was influence of AS soils, but it was largely masked by eroded phyllosilicates. Consequently, rivers draining clay plains sensitive to erosion, like those in SW Finland, have generally high background metal concentrations due to erosion. Thus, relying on only semi-dissolved (<0.45 μm) concentrations obtained in routine monitoring, or geochemical modelling based on such data, can lead to a great overestimation of the water toxicity in this environment. The potentially toxic elements that are of concern in AS soil areas will ultimately be precipitated in the recipient estuary or sea, where the acidic metalrich river water will gradually be diluted/neutralised with brackish seawater. Along such a rising pH gradient Al, Cu and U will precipitate first together with organic matter closest to the river mouth. Manganese is relatively persistent in solution and, thus, precipitates further down the estuary as Mn oxides together with elements such as Ba, Cd, Co, Cu and Ni. Iron oxides, on the contrary, are not important scavengers of metals in the estuary, they are predicted to be associated only with As and PO4.

Exploration and Design of Power-Efficient Networked Many-Core Systems

Multiprocessing is a promising solution to meet the requirements of near future applications. To get full benefit from parallel processing, a manycore system needs efficient, on-chip communication architecture. Networkon- Chip (NoC) is a general purpose communication concept that offers highthroughput, reduced power consumption, and keeps complexity in check by a regular composition of basic building blocks. This thesis presents power efficient communication approaches for networked many-core systems. We address a range of issues being important for designing power-efficient manycore systems at two different levels: the network-level and the router-level. From the network-level point of view, exploiting state-of-the-art concepts such as Globally Asynchronous Locally Synchronous (GALS), Voltage/ Frequency Island (VFI), and 3D Networks-on-Chip approaches may be a solution to the excessive power consumption demanded by today’s and future many-core systems. To this end, a low-cost 3D NoC architecture, based on high-speed GALS-based vertical channels, is proposed to mitigate high peak temperatures, power densities, and area footprints of vertical interconnects in 3D ICs. To further exploit the beneficial feature of a negligible inter-layer distance of 3D ICs, we propose a novel hybridization scheme for inter-layer communication. In addition, an efficient adaptive routing algorithm is presented which enables congestion-aware and reliable communication for the hybridized NoC architecture. An integrated monitoring and management platform on top of this architecture is also developed in order to implement more scalable power optimization techniques. From the router-level perspective, four design styles for implementing power-efficient reconfigurable interfaces in VFI-based NoC systems are proposed. To enhance the utilization of virtual channel buffers and to manage their power consumption, a partial virtual channel sharing method for NoC routers is devised and implemented. Extensive experiments with synthetic and real benchmarks show significant power savings and mitigated hotspots with similar performance compared to latest NoC architectures. The thesis concludes that careful codesigned elements from different network levels enable considerable power savings for many-core systems.

On Dynamic Monitoring Methods for Networks-on-Chip

Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.

Pallomaisen rullalaakerin vauriotutkimus kartonkikoneen kiertoöljyvoidellulla kuivatusosalla

Tämä työ on tehty Stora Enson Imatran kartonkitehtaan kunnossapidosta vastaavalle Efora Oy:lle. Tavoitteena oli selvittää syy Imatran Kartonkikone 5:n kuivatussylinterien laakerivaurioiden suureen määrään verrattuna tehtaiden kolmeen muuhun kartonkikoneeseen. Tutkimuksissa keskityttiin laakerien käyttöolosuhteisiin. Syyn selvittämiseksi työssä vertailtiin eri kartonkikoneiden kiertoöljyvoitelujärjestelmiä, voiteluöljyjä, voiteluolosuhteita, öljyjen kuntoa ja kunnon seurantaa. Myös laakereihin kohdistuvia kuormia arvioitiin. Alan kirjallisuuden avulla on käyty läpi kartonkikoneen rakennetta ja toimintaa tarvittavassa laajuudessa, voitelun ja laakerin vaurioitumisen teoriaa sekä voiteluaineiden ominaisuuksien ja koostumuksen perusteita. Vertailevissa tutkimuksissa ei löytynyt vauriomäärien eroja selittäviä eroavaisuuksia Imatran tehtaiden eri kartonkikoneiden välillä, joskin Kartonkikone 5:n kiertovoiteluöljyn puhtaustaso oli muita Imatran kartonkikoneita heikompi. Laakerikuormien osalta havaittiin joidenkin laakerien käyvän laakerille asetetun vähimmäiskuorman alittavilla kuormituksilla. Vähimmäiskuormaa pienempi radiaalikuorma voi johtaa laakerin virheelliseen toimintaan ja edelleen vaurioitumiseen. Voiteluolosuhteet todettiin erittäin vaikeiksi ja niillä on epäilemättä vaikutusta voiteluöljyn ja laakerien lyhentyneeseen käyttöikään.

On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

Cell Model Systems in Characterizing Alpha2-Adrenoceptors as Drug Targets.

The three alpha2-adrenoceptor (alpha2-AR) subtypes belong to the G protein-coupled receptor superfamily and represent potential drug targets. These receptors have many vital physiological functions, but their actions are complex and often oppose each other. Current research is therefore driven towards discovering drugs that selectively interact with a specific subtype. Cell model systems can be used to evaluate a chemical compound's activity in complex biological systems. The aim of this thesis was to optimize and validate cell-based model systems and assays to investigate alpha2-ARs as drug targets. The use of immortalized cell lines as model systems is firmly established but poses several problems, since the protein of interest is expressed in a foreign environment, and thus essential components of receptor regulation or signaling cascades might be missing. Careful cell model validation is thus required; this was exemplified by three different approaches. In cells heterologously expressing alpha2A-ARs, it was noted that the transfection technique affected the test outcome; false negative adenylyl cyclase test results were produced unless a cell population expressing receptors in a homogenous fashion was used. Recombinant alpha2C-ARs in non-neuronal cells were retained inside the cells, and not expressed in the cell membrane, complicating investigation of this receptor subtype. Receptor expression enhancing proteins (REEPs) were found to be neuronalspecific adapter proteins that regulate the processing of the alpha2C-AR, resulting in an increased level of total receptor expression. Current trends call for the use of primary cells endogenously expressing the receptor of interest; therefore, primary human vascular smooth muscle cells (SMC) expressing alpha2-ARs were tested in a functional assay monitoring contractility with a myosin light chain phosphorylation assay. However, these cells were not compatible with this assay due to the loss of differentiation. A rat aortic SMC cell line transfected to express the human alpha2B-AR was adapted for the assay, and it was found that the alpha2-AR agonist, dexmedetomidine, evoked myosin light chain phosphorylation in this model.

Thermal-Aware Networked Many-Core Systems

Advancements in IC processing technology has led to the innovation and growth happening in the consumer electronics sector and the evolution of the IT infrastructure supporting this exponential growth. One of the most difficult obstacles to this growth is the removal of large amount of heatgenerated by the processing and communicating nodes on the system. The scaling down of technology and the increase in power density is posing a direct and consequential effect on the rise in temperature. This has resulted in the increase in cooling budgets, and affects both the life-time reliability and performance of the system. Hence, reducing on-chip temperatures has become a major design concern for modern microprocessors. This dissertation addresses the thermal challenges at different levels for both 2D planer and 3D stacked systems. It proposes a self-timed thermal monitoring strategy based on the liberal use of on-chip thermal sensors. This makes use of noise variation tolerant and leakage current based thermal sensing for monitoring purposes. In order to study thermal management issues from early design stages, accurate thermal modeling and analysis at design time is essential. In this regard, spatial temperature profile of the global Cu nanowire for on-chip interconnects has been analyzed. It presents a 3D thermal model of a multicore system in order to investigate the effects of hotspots and the placement of silicon die layers, on the thermal performance of a modern ip-chip package. For a 3D stacked system, the primary design goal is to maximise the performance within the given power and thermal envelopes. Hence, a thermally efficient routing strategy for 3D NoC-Bus hybrid architectures has been proposed to mitigate on-chip temperatures by herding most of the switching activity to the die which is closer to heat sink. Finally, an exploration of various thermal-aware placement approaches for both the 2D and 3D stacked systems has been presented. Various thermal models have been developed and thermal control metrics have been extracted. An efficient thermal-aware application mapping algorithm for a 2D NoC has been presented. It has been shown that the proposed mapping algorithm reduces the effective area reeling under high temperatures when compared to the state of the art.

Automatic traffic sign inventory- and condition analysis

This thesis researches automatic traffic sign inventory and condition analysis using machine vision and pattern recognition methods. Automatic traffic sign inventory and condition analysis can be used to more efficient road maintenance, improving the maintenance processes, and to enable intelligent driving systems. Automatic traffic sign detection and classification has been researched before from the viewpoint of self-driving vehicles, driver assistance systems, and the use of signs in mapping services. Machine vision based inventory of traffic signs consists of detection, classification, localization, and condition analysis of traffic signs. The produced machine vision system performance is estimated with three datasets, from which two of have been been collected for this thesis. Based on the experiments almost all traffic signs can be detected, classified, and located and their condition analysed. In future, the inventory system performance has to be verified in challenging conditions and the system has to be pilot tested.

Formal development of resilient distributed systems

Resilience is the property of a system to remain trustworthy despite changes. Changes of a different nature, whether due to failures of system components or varying operational conditions, significantly increase the complexity of system development. Therefore, advanced development technologies are required to build robust and flexible system architectures capable of adapting to such changes. Moreover, powerful quantitative techniques are needed to assess the impact of these changes on various system characteristics. Architectural flexibility is achieved by embedding into the system design the mechanisms for identifying changes and reacting on them. Hence a resilient system should have both advanced monitoring and error detection capabilities to recognise changes as well as sophisticated reconfiguration mechanisms to adapt to them. The aim of such reconfiguration is to ensure that the system stays operational, i.e., remains capable of achieving its goals. Design, verification and assessment of the system reconfiguration mechanisms is a challenging and error prone engineering task. In this thesis, we propose and validate a formal framework for development and assessment of resilient systems. Such a framework provides us with the means to specify and verify complex component interactions, model their cooperative behaviour in achieving system goals, and analyse the chosen reconfiguration strategies. Due to the variety of properties to be analysed, such a framework should have an integrated nature. To ensure the system functional correctness, it should rely on formal modelling and verification, while, to assess the impact of changes on such properties as performance and reliability, it should be combined with quantitative analysis. To ensure scalability of the proposed framework, we choose Event-B as the basis for reasoning about functional correctness. Event-B is a statebased formal approach that promotes the correct-by-construction development paradigm and formal verification by theorem proving. Event-B has a mature industrial-strength tool support { the Rodin platform. Proof-based verification as well as the reliance on abstraction and decomposition adopted in Event-B provides the designers with a powerful support for the development of complex systems. Moreover, the top-down system development by refinement allows the developers to explicitly express and verify critical system-level properties. Besides ensuring functional correctness, to achieve resilience we also need to analyse a number of non-functional characteristics, such as reliability and performance. Therefore, in this thesis we also demonstrate how formal development in Event-B can be combined with quantitative analysis. Namely, we experiment with integration of such techniques as probabilistic model checking in PRISM and discrete-event simulation in SimPy with formal development in Event-B. Such an integration allows us to assess how changes and di erent recon guration strategies a ect the overall system resilience. The approach proposed in this thesis is validated by a number of case studies from such areas as robotics, space, healthcare and cloud domain.

Suorituskyvyn analysointijärjestelmä teknologiateollisuuden pk-yritykselle

Monesti yritysjohtajan on vaikea hahmottaa, mitä kaikkia ulottuvuuksia ja menetelmiä suorituskyvyn analysointiin liittyy. Pelkkään talouteen keskittyvä johtaminen edustaa hyvin kapeaa näkökulmaa yrityksen toiminnasta ja voi lopulta johtaa yrityksen vääriin valintoihin ja hyvin kohtalokkaisiin virhearviointeihin. Suorituskyvyn mittaamisella ja analysoimisella saadaan kokonaisvaltainen näkemys yrityksen toiminnasta ja sen tilasta. Yrityksen suorituskykyä pystytään tarkastelemaan hyvin monella tavalla ja erilaisista näkökulmista. Tutkimuksen päätavoitteena on selvittää millainen suorituskyvyn analysointijärjestelmä soveltuu teknologiateollisuuden pk-yritykselle. Alatavoitteena on tutkia millaiset mittaus- ja johtamistarpeet ovat toimialalle tyypillisiä (1) sekä miten toiminnanohjausjärjestelmä ja suori-tuskyvyn mittaristo voidaan integroida toisiinsa (2). Case-yritykselle rakennetaan suorituskyvyn mittaristo ja verrataan sitä toiminnanohjausjärjestelmään sekä selvitetään mittariston tarpeellisuutta Case-yritykselle. Teknologiateollisuuden pk-yrityksille ei voida suoraan määrittää sopivaa suorituskyvyn ana-lysointijärjestelmää. BSC osoittautui kuitenkin parhaimmaksi valinnaksi. BSC pakottaa pk-yrityksiä huomioimaan useampi suorituskyvyn osa-alue. BSC ei myöskään tarvitse montaa mittaria kuvaamaan suorituskyvyn osa-alueita. Tutkimuksessa selvisi hyvin paljon suorituskykyyn vaikuttavia tekijöitä. Projektiluonteisuuden vuoksi case-yrityksen projektiseurantaa kehitettiin ja rakennettiin BSC-pohjainen suorituskyvyn analysointijärjestelmä.

Interoperability for IoT Health Systems Using HL7 Standard

Internet of Things or IoT is revolutionizing the world we are living in, similarly the way Internet and the web did few decades ago. It is changing how we interact with the things surrounding us. Electronic health and remote patient monitoring are the ways of utilizing these technological improvements towards the healthcare. There are many applications of IoT in eHealth such as, it will open the gate to provide healthcare to the remote areas of the world, where healthcare through traditional hospital systems cannot be provided. To connect these new eHealth IoT systems with the existing healthcare information systems, we can use the existing interoperability standards commonly used in healthcare information systems. In this thesis we implemented an eHealth IoT system based on Health Level 7 interoperability standard for continuous data transmission. There is not much previous work done in implementing the HL7 for continuous sensor data transmission. Some of the previous work was limited to sensors which are not continuous in nature and some of it is only theatrical architecture. This thesis aims to prove that it is possible to implement an eHealth IoT system by using sensors which require continues data transmission, such as respiratory sensors, and to connect it with the existing eHealth information system semantically by using HL7 interoperability standard. This system will be beneficial in implementing eHealth IoT systems for those patients, who requires continuous healthcare personal monitoring. This includes elderly people and patients, whose health need to be monitored constantly. To implement the architecture, HL7 v2.5 is selected due to its ease of implementation and low size. We selected some open source technologies because of their open licenses and large developer community. We will also review the most efficient technology available in every layer of eHealth IoT system and will propose an efficient system.

Life cycle management of TVO nuclear power plant

Tämä diplomityö tutkii eri elinkaarihallinnan menetelmiä ja vertaa niitä TVO:n menetelmiin. Lisäksi TVO:n prosessin ongelmakohdat tunnistetaan ja niihin esitetään ratkaisuja. Vertailukohteina toimii ydinvoimateollisuuden lisäksi vesivoima, fossiiliset voimalaitokset sekä paperiteollisuus. Sähkön hinnan jatkaessa laskuaan on elinkaariajattelusta tullut ajankohtaista myös ydinvoimayhtiöille. Ydinvoimalaitoksien pitkän suunnitellun käyttöiän ansiosta laitoksen elinkaaren aikana voi tapahtua useita asioita, jotka vaikuttavat laitoksen investointitarpeisiin. Turvallisen sähköntuotannon varmistamiseksi eri laitososia on joko muokattava tai uusittava. Elinkaariajatteluun kuuluu tehokas laitoksen kunnon valvonta, laitoksen ikääntymiseen vaikuttavien ilmiöiden tunnistaminen, sekä ikääntymistä hillitsevien toimenpiteiden pitkän tähtäimen suunnittelu. Hyvällä ennakkosuunnittelulla pyritään varmistamaan se, että laitoksella voidaan tuottaa sähköä koko sen jäljellä olevan käyttöiän aikana. Kun tarpeiden tunnistus ja suunnittelu tehdään hyvissä ajoin mahdollistetaan myös investointien optimointi. Paras hyöty pyritään saamaan ajoittamalla oikeat investoinnit oikeaan aikaan.

Activity-based life cycle costing model for cost estimation and monitoring – Case: manned and autonomous dry bulk carrier

Recent developments in automation, robotics and artificial intelligence have given a push to a wider usage of these technologies in recent years, and nowadays, driverless transport systems are already state-of-the-art on certain legs of transportation. This has given a push for the maritime industry to join the advancement. The case organisation, AAWA initiative, is a joint industry-academia research consortium with the objective of developing readiness for the first commercial autonomous solutions, exploiting state-of-the-art autonomous and remote technology. The initiative develops both autonomous and remote operation technology for navigation, machinery, and all on-board operating systems. The aim of this study is to develop a model with which to estimate and forecast the operational costs, and thus enable comparisons between manned and autonomous cargo vessels. The building process of the model is also described and discussed. Furthermore, the model’s aim is to track and identify the critical success factors of the chosen ship design, and to enable monitoring and tracking of the incurred operational costs as the life cycle of the vessel progresses. The study adopts the constructive research approach, as the aim is to develop a construct to meet the needs of a case organisation. Data has been collected through discussions and meeting with consortium members and researchers, as well as through written and internal communications material. The model itself is built using activity-based life cycle costing, which enables both realistic cost estimation and forecasting, as well as the identification of critical success factors due to the process-orientation adopted from activity-based costing and the statistical nature of Monte Carlo simulation techniques. As the model was able to meet the multiple aims set for it, and the case organisation was satisfied with it, it could be argued that activity-based life cycle costing is the method with which to conduct cost estimation and forecasting in the case of autonomous cargo vessels. The model was able to perform the cost analysis and forecasting, as well as to trace the critical success factors. Later on, it also enabled, albeit hypothetically, monitoring and tracking of the incurred costs. By collecting costs this way, it was argued that the activity-based LCC model is able facilitate learning from and continuous improvement of the autonomous vessel. As with the building process of the model, an individual approach was chosen, while still using the implementation and model building steps presented in existing literature. This was due to two factors: the nature of the model and – perhaps even more importantly – the nature of the case organisation. Furthermore, the loosely organised network structure means that knowing the case organisation and its aims is of great importance when conducting a constructive research.

Using ICT Energy consumption for monitoring ICT architecture

Energy efficient policies are being applied to network protocols, devices and classical network management systems. Researchers have already studied in depth each of those fields, including for instance a long monitoring processes of various number of individual ICT equipment from where power models are constructed. With the development of smart meters and emerging protocols such as SNMP and NETCONF, currently there is an open field to couple the power models, translated to the expected behavior, with the realtime energy measurements. The goal is to derive a comparison on the power data between both of the processes in the direction of detection for possible deviations on the expected results. The logical assumption is that a fault in the usage of a particular device will not only increase its own energy usage, but also may cause additional consumption on the other devices part of the network. A platform is developed to monitor and analyze the retrieved power data of a simulated enterprise ICT infrastructure. Moreover, smart algorithms are developed which are aware of the different states that are occurring on each device during their typical use phase, as well as to detect and isolate possible anomalies. The produced results are obtained and validated with the use of Cisco switches and routers, Dell Precision stations and Raritan PDU as part of the monitored infrastructure.