Charikleia Papatsimpa

Bio: Charikleia Papatsimpa is an academic researcher from Eindhoven University of Technology. The author has contributed to research in topics: Building automation & Hidden Markov model. The author has an hindex of 6, co-authored 18 publications receiving 75 citations.

Personalized Office Lighting for Circadian Health and Improved Sleep.

Abstract: In modern society, the average person spends more than 90% of their time indoors. However, despite the growing scientific understanding of the impact of light on biological mechanisms, the existing light in the built environment is designed predominantly to meet visual performance requirements only. Lighting can also be exploited as a means to improve occupant health and well-being through the circadian functions that regulate sleep, mood, and alertness. The benefits of well-lit spaces map across other regularly occupied building types, such as residences and schools, as well as patient rooms in healthcare and assisted-living facilities. Presently, Human Centric Lighting is being offered based on generic insights on population average experiences. In this paper, we suggest a personalized bio-adaptive office lighting system, controlled to emit a lighting recipe tailored to the individual employee. We introduce a new mathematical optimization for lighting schedules that align the 24-h circadian cycle. Our algorithm estimates and optimizes parameters in experimentally validated models of the human circadian pacemaker. Moreover, it constrains deviations from the light levels desired and needed to perform daily activities. We further translate these into general principles for circadian lighting. We use experimentally validated models of the human circadian pacemaker to introduce a new algorithm to mathematically optimize lighting schedules to achieve circadian alignment to the 24-h cycle, with constrained deviations from the light levels desired for daily activities. Our suggested optimization algorithm was able to translate our findings into general principles for circadian lighting. In particular, our simulation results reveal: (1) how energy constrains drive the shape of optimal lighting profiles by dimming the light levels in the time window that light is less biologically effective; (2) how inter-individual variations in the characteristic internal duration of the day shift the timing of optimal lighting exposure; (3) how user habits and, in particular, late-evening light exposure result in differentiation in late afternoon office lighting.

The interindividual variability of sleep timing and circadian phase in humans is influenced by daytime and evening light conditions

Abstract: Human cognitive functioning shows circadian variations throughout the day. However, individuals largely differ in their timing during the day of when they are more capable of performing specific tasks and when they prefer to sleep. These interindividual differences in preferred temporal organization of sleep and daytime activities define the chronotype. Since a late chronotype is associated with adverse mental and physical consequences, it is of vital importance to study how lighting environments affect chronotype. Here, we use a mathematical model of the human circadian pacemaker to understand how light in the built environment changes the chronotype distribution in the population. In line with experimental findings, we show that when individuals spend their days in relatively dim light conditions, this not only results in a later phase of their biological clock but also increases interindividual differences in circadian phase angle of entrainment and preferred sleep timing. Increasing daytime illuminance results in a more narrow distribution of sleep timing and circadian phase, and this effect is more pronounced for longer photoperiods. The model results demonstrate that modern lifestyle changes the chronotype distribution towards more eveningness and more extreme differences in eveningness. Such model-based predictions can be used to design guidelines for workplace lighting that help limiting circadian phase differences, and craft new lighting strategies that support human performance, health and wellbeing.

Dynamic Performance Analysis of IEEE 802.15.4 Networks under Intermittent Wi-Fi Interference

Abstract: A ZigBee (802.15.4) lighting network is potentially vulnerable to interference by other wireless technologies that operate in the same Industrial, Scientific and Medical (ISM) frequency band, such as Wi-Fi (802.11). Therefore the study of coexistence between IEEE 802.15.4 and IEEE 802.11/Wi-Fi is becoming more relevant than ever. In this area, literature approaches to the co-existence issue currently fall into two main categories: experimental or simulation results and analytical models which are either asymptotic (e.g., using Bianchi's assumption) and/or stationary. In contrast, in this paper we present an analytical framework in which a comprehensive study of the dynamic influence of Wi-Fi interference on ZigBee networks of arbitrary size becomes possible. We first present an application of mean field approximation to an intractable Markov model of ZigBee networks. We use this modeling approach to investigate the effect of the Wi-Fi traffic pattern on the ZigBee network performance. By taking this dynamic interaction into account, we notice major performance differences depending on the type of traffic. It also reveals that even light traffic patterns, that offer long gaps of inactivity, can hamper the ZigBee performance significantly more than previously reported Wi-Fi coexistence studies suggest.

Energy efficient communication in smart building WSN running distributed Hidden Markov chain presence detection algorithm

Abstract: Occupancy detection in smart buildings suffers from high sensor unreliability. The combination of data from multiple sensors can largely improve reliability. However, battery-powered sensor nodes have communication limitations. This paper addresses the problem of presence detection in a building as Distributed Sensing of a Hidden Markov Model (DS-HMM). Optimal solutions require excessive communication over a perfectly reliable channel. We propose and investigate an efficient transmission policy, jointly with a fusion algorithm, to merge data from various HMMs running separately on all sensor nodes. The algorithm showed improved performance and potential energy savings in a real world set-up, where user presence and sensor errors may not exactly follow idealized model assumptions.

The interaction between humans and buildings for energy efficiency: A critical review

Abstract: Buildings consume energy for different purposes. One core function is to provide healthy and comfortable living conditions for the humans that inhabit these buildings. The associated energy use is significant: taken together, buildings are responsible for roughly 40% of the world’s total annual energy consumption. This large percentage makes the built environment an important target for researchers, policy makers, innovators and others who aim to decrease energy consumption and the associated emissions of Greenhouse Gases (GHG). Unfortunately, the significant body of research on energy efficient buildings conducted since the 1970s has had only a limited impact on the overall energy use of the sector, and this remains a serious concern. The energy use of buildings shows a strong correlation with the activities of the building occupants. A key factor that makes it hard to curb building energy use is a lack of understanding of building occupant behaviour. This paper reviews research on building occupant behaviour in two stages. The first stage reviews important issues, milestones, methodologies used, building types analysed and progress achieved related to the topic, as reported in the most frequently cited papers. The second stage focuses on recent work in the area and investigates ‘state of the art’ developments in terms of questions asked and solutions proposed. The aim is to identify problems and knowledge gaps in the field for future projection. Recent research on the topic is analysed, taking account of methodologies, building types, locations, keywords, data sampling and survey size. Based on a critical analysis of the literature, the following outcomes can be reported: research on building occupant behaviour relies strongly on quantitative methods, but studies are mostly located in the northern hemisphere and in developed and high-income countries. The dominant research topics associated with occupant behaviour are energy demand and thermal comfort, followed by retrofit and renovation. Most research focuses on technical aspects rather than socio-economic issues. Current research is mostly limited to studies of single buildings and typically lacks data-gathering standards, which makes it hard to conduct cross cultural data comparisons. Most research concentrates on individual topics, such as window, door and blind adjustments, effects of Heating Ventilating Air Condition (HVAC) systems etc. and does not provide a wider, holistic view that can be linked to social and economic factors.

Design and Application of a Smart Lighting System Based on Distributed Wireless Sensor Networks

Abstract: Buildings have been an important energy consuming sector, and inefficient controlling of lights can result in wastage of energy in buildings. The aim of the study is to reduce energy consumption by implementing a smart lighting system that integrates sensor technologies, a distributed wireless sensor network (WSN) using ZigBee protocol, and illumination control rules. A sensing module consists of occupancy sensors, including passive infrared (PIR) sensors and microwave Doppler sensors, an ambient light sensor, and lighting control rules. The dimming level of each luminaire is controlled by rules taking into consideration occupancy and daylight harvesting. The performance of the proposed system is evaluated in two scenarios, a metro station and an office room, and the average energy savings are about 45% and 36%, respectively. The effects of different factors on energy savings are analyzed, including people flow density, weather, desired illuminance, and the number of people in a room. Experimental results demonstrate the robustness of the proposed system and its ability to save energy consumption. The study can benefit the development of intelligent and sustainable buildings.

When artificial intelligence meets building energy efficiency, a review focusing on zero energy building

Abstract: Building energy efficiency, as a traditional field which has been existing for decades performs a prosperous needs with diversity of corresponding methods. In the flow of artificial intelligence (AI) background, where does the building energy efficiency advance and how does it emphasize? This question seems to become more significant with the blueprints of zero energy building implementation issued by many countries. The major objective of this research is to review, analyze and identify the performance of AI based applications in buildings, especially for building energy efficiency and zero energy building. Based on the present research trends, the possible changes AI based approach brings to related laws, regulations and standards are firstly analyzed. The main aspects of the AI based approach infrastructure in buildings is thoroughly reviewed and compared. IoT based sensor applications for thermal comfort, platforms and algorithms for building multi energies control, and forecasting methods for building load, subsystem performance and structure safety are summarized. To provide more optimal references for zero energy building solutions, the AI based approach in zero energy building is then predicted in detail, with particular analysis of occupant presence and behaviors. Finally, the future directions of the research on AI based applications for zero energy building implementation are summarized.