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Estimating occupancy heat gains from CO2 measurements

gains and internal gains from appliances,heat gains from occupants are an importantsource contributing to space heating indomestic buildings. It is necessary toconsciously consider all of these heat gainswhen aiming at accurately estimating theheat loss coefficient (HLC) of a building.Whilst sensor technology and algorithms areavailable to quantify the contribution of theheating system, solar gains and electricalappliances, the accurate estimation of thesensible heat gain from occupants ischallenging due to its stochastic character.

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Estimating occupancy heat gains from CO2 measurements

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On the feasibility of using a multi-parameter sensor for the inline characterisation of medicine mixtures

Abstract geschreven door R.J. Dijkink (Saxion), J.C. Lötters (Universiteit van Twente & Bronkhorst High-Tech BV), B.I. van den Berg (Medical Spectrum Twente) en C.A.J. Damen (Saxion). Initial investigations into the use of a MEMS based multi-parameter sensor for the characterization of medicine mixtures are presented. The current results show good results for density and mediocre results for heat capacity. Viscosity measurements have not yet produced any usable results. However there are clear flaws in the setup which could be the cause of this and which will no

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On the feasibility of using a multi-parameter sensor for the inline characterisation of medicine mixtures

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Weather stations comparison

This report summarizes the result of the comparison between 4 weather stations: 2 Kestrels 5400 Heat Stress and 2 Davis Vantage Pro2. The measurements were performed from the 08/04/2019 to 11/04/2019 on the rooftop of the Benno Premselahuis from the Hogeschool van Amsterdam.

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Mapping swarms of resource-limited sensor motes: Solely using distance measurements and non-unique identifiers

This work is on 3-D localization of sensor motes in massive swarms based solely on 1-D relative distance-measurements between neighbouring motes. We target applications in remote and difficult-to-access environments such as the exploration and mapping of the interior of oil reservoirs where hundreds or thousands of motes are used. These applications bring forward the need to use highly miniaturized sensor motes of less than 1 centimeter, thereby significantly limiting measurement and processing capabilities. These constraints, in combination with additional limitations posed by the environments, impede the communication of unique hardware identifiers, as well as communication with external, fixed beacons.

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Robust sensor cloud localization from range measurements

This work provides a feasibility study on estimating the 3-D locations of several thousand miniaturized free-floating sensor platforms. The localization is performed on basis of sparse ultrasound range measurements between sensor platforms and without the use of beacons. We show that this task can be viewed as a specific type of pose graph optimization. The main challenge is robustly estimating an initial pose graph, that models the locations of sensor platforms. For this, we introduce a novel graph growing strategy that uses random sample consensus in alternation with non-linear refinement. The theoretical properties of our sensor cloud localization method are analyzed and its robustness is investigated using simulations. These simulations are based on inlier-outlier measurement models and focus on the application of subterranean 3-D mapping of liquid environments, such as pipe infrastructures and oil wells.

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Monitoring body temperature and activity in sows using a sensor-based telemetric system

Improving estrus detection accuracy could improve sow conception rates,leading to higher production efficiency. Current observation-based estrusdetection practices are labor intensive and less accurate. Around estrus, bodytemperature and activity change. Therefore in this study a telemetric monitoringsystem for body temperature and activity was tested. Firstly Templant2 sensors(TeleMetronics) were validated under lab conditions for temperatures from 35°Cto 45°C, using a water basin with a Julabo heater and a P600 thermometer.Activity measurements were validated with the sensors attached to a stick,simulating sow movements. Secondly, sensors were attached externally to 4gilts and 4 sows for 30 minutes, testing functionality. Thirdly, activity of sowswas recorded manually for 3 days around estrus. Results showed that under labconditions temperature results of sensors, heater and thermometer were highlycorrelated (linear regression, R2=0,96; slope 1,1). Simulated activitiescorresponded consistently with peaks in sensor values. Activity was measuredreliably with the sensor attached externally to the sows. On the farm, sowsshowed more activity (manual observations, P<0.05 for standing up, lying down,sitting down and walking) the day before insemination. We conclude thatmonitoring activity and body temperature is a promising tool for estrousdetection in sows.

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Where To Go?

CC-BY-NC-ND This paper was presented at the IADIS Multi Conference on Computer Science and Information Systems MCCSIS2020 There is an increasing interest in indoor occupation and guidance information for business and societal purposes. Scientific literature has paid attention to various ways of detecting occupation using different sensors as data source including various algorithms for estimating occupation rates from this data. Gaining meaningful insights from the data still faces challenges because the potential benefits are not well understood. This study presents a proof-of-concept of an indoor occupation information system, following the design science methodology. We review various types of sensor data that are typically available or easy-to-install in buildings such as offices, classrooms and meeting rooms. This study contributes to current research by incorporating business requirements taken from expert interviews and tackling one of the main barriers for business by designing an affordable system on a common existing infrastructure. We believe that occupation information systems call for further research, in particular also in the context of social distancing because of covid19.

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Improving indoor localisation of firefighters based on inertial measurements

Knowing firefighters’ locations in a burning building would dramatically improve their safety. In this study from the Saxion Research Centre for Design and Technology in the Firebee project, an algorithm was developed and tested to enhance the estimation of a person’s location, based on inertial measurements combined with measurements of the earth’s magnetic field. The developed algorithm is an extension of the zero velocity update technique. Without any enhancements, the accuracy of the estimation is in the order of several meters after measuring for only a few seconds. With enhancements, the accuracy improved to be within five meters after measuring for ten minutes. Our result demonstrated that it is possible to determine in which room and on which floor a person is after ten minutes. Major improvements were observed in the estimation of the sensor’s height. The results are promising and the following phases of the project focus on improving the solution and on developing the concept into a practically applicable system.

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Producten 659

Estimating occupancy heat gains from CO2 measurements

On the feasibility of using a multi-parameter sensor for the inline characterisation of medicine mixtures

Weather stations comparison

Mapping swarms of resource-limited sensor motes: Solely using distance measurements and non-unique identifiers

Robust sensor cloud localization from range measurements

Monitoring body temperature and activity in sows using a sensor-based telemetric system

Where To Go?

Improving indoor localisation of firefighters based on inertial measurements

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Producten 659

Estimating occupancy heat gains from CO2 measurements

On the feasibility of using a multi-parameter sensor for the inline characterisation of medicine mixtures

Weather stations comparison

Mapping swarms of resource-limited sensor motes: Solely using distance measurements and non-unique identifiers

Robust sensor cloud localization from range measurements

Monitoring body temperature and activity in sows using a sensor-based telemetric system

Where To Go?

Improving indoor localisation of firefighters based on inertial measurements