Open Source Building Science Sensors (OSBSS): A low-cost Arduino-based platform for long-term indoor environmental data collection

1AbstractThe handling of oxygen sensitive samples and growth of obligate anaerobic organisms requires the stringent exclusion of oxygen, which is omnipresent in our normal atmospheric environment. Anaerobic workstations (aka. Glove boxes) enable the handling of oxygen sensitive samples during complex procedures, or the long-term incubation of anaerobic organisms. Depending on the application requirements, commercial workstations can cost up to 60.000 €. Here we present the complete build instructions for a highly adaptive, Arduino based, anaerobic workstation for microbial cultivation and sample handling, with features normally found only in high cost commercial solutions. This build can automatically regulate humidity, H2 levels (as oxygen reductant), log the environmental data and purge the airlock. It is built as compact as possible to allow it to fit into regular growth chambers for full environmental control. In our experiments, oxygen levels during the continuous growth of oxygen producing cyanobacteria, stayed under 0.03 % for 21 days without needing user intervention. The modular Arduino controller allows for the easy incorporation of additional regulation parameters, such as CO2 concentration or air pressure. This paper provides researchers with a low cost, entry level workstation for anaerobic sample handling with the flexibility to match their specific experimental needs.Specifications table[please fill in right-hand column of the table below]

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Monitoring and Calibration of Long Term Mooring System Design Assumptions Through Use of AIS and Weather Data

10.4043/31079-ms ◽

2021 ◽

Author(s):

Dag Børre Lillestøl ◽

Odd Torbjørn Kårvand ◽

Are Torstensen

Keyword(s):

Low Cost ◽

Environmental Data ◽

Weather Data ◽

Mooring System ◽

System Behavior ◽

Original Design ◽

Actual System ◽

Early Failures ◽

And Performance

Abstract This paper outlines an approach on how to improve the mooring integrity of existing long term mooring systems by using existing and commercially available data. It will be demonstrated how the use of AIS and hindcast weather data can be used to increase understanding of mooring systems and to monitor and quantify gaps between "as-designed", "as-installed" and "as-is" of a long term mooring system. Long term moored units have traditionally suffered from many early failures, caused by damages and errors introduced in the installation phase, and costly and unnecessary "late in life" failures. A fact rated high on the agenda of the underwriters. Numerous papers have been written on this topic, but it is only in recent years the industry have started to ensure that systems are inspected to a sufficient degree with respect to the physical condition, taking these learnings into account. However, the second important element, the calibration of the mooring analysis vs. actual vessel and mooring system behavior/performance, have not yet gotten the attention required. Deviations from the intended design are introduced in the installation phase of a mooring system. In addition, the design assumptions will never be fully accurate. The gap between the design assumptions and the actual system will increase over time, and the industry today do not focus on mapping and quantifying the effect of this gap sufficiently. The described method explains how one can introduce a pro-active approach, without installing onboard equipment, but rather utilizing algorithms on existing data and design documentation. This paper focuses on the use of AIS data in combination with historic weather/environmental data and seek to demonstrate how this low-cost method can provide useful information with respect to the mooring system. To emphasize the mapped importance of such calibrations, the July 2021 Edition of the in-service DNV Class Rules, DNVGL-OS-0300, formally introduces requirements to calibration of design assumptions of long term mooring units through use of survey data, service history and actual mooring system behavior in order to ensure a unit's mooring system condition and performance is known in light of the original design assumptions.

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Data Gathering from a Multimodal Dense Underwater Acoustic Sensor Network Deployed in Shallow Fresh Water Scenarios

Journal of Sensor and Actuator Networks ◽

10.3390/jsan8040055 ◽

2019 ◽

Vol 8 (4) ◽

pp. 55 ◽

Cited By ~ 1

Author(s):

Alberto Signori ◽

Filippo Campagnaro ◽

Fabian Steinmetz ◽

Bernd-Christian Renner ◽

Michele Zorzi

Keyword(s):

Data Collection ◽

Low Cost ◽

World Ocean ◽

Environmental Data ◽

Sensor Nodes ◽

Real Field ◽

Acoustic Sensor ◽

Adaptive Mechanism ◽

Underwater Acoustic ◽

Inspection Service

The Robotic Vessels as-a-Service (RoboVaaS) project intends to exploit the most advanced communication and marine vehicle technologies to revolutionize shipping and near-shore operations, offering on-demand and cost-effective robotic-aided services. In particular, the RoboVaaS vision includes a ship hull inspection service, a quay walls inspection service, an antigrounding service, and an environmental and bathymetry data collection service. In this paper, we present a study of the underwater environmental data collection service, performed by a low-cost autonomous vehicle equipped with both a commercial modem and a very low-cost acoustic modem prototype, the smartPORT Acoustic Underwater Modem (AHOI). The vehicle mules the data from a network of low cost submerged acoustic sensor nodes to a surface sink. To this end, an underwater acoustic network composed by both static and moving nodes has been implemented and simulated with the DESERT Underwater Framework, where the performance of the AHOI modem has been mapped in the form of lookup tables. The performance of the AHOI modem has been measured near the Port of Hamburg, where the RoboVaaS concept will be demonstrated with a real field evaluation. The transmission with the commercial modem, instead, has been simulated with the Bellhop ray tracer thanks to the World Ocean Simulation System (WOSS), by considering both the bathymetry and the sound speed profile of the Port of Hamburg. The set up of the polling-based MAC protocol parameters, such as the maximum backoff time of the sensor nodes, appears to be crucial for the network performance, in particular for the low-cost low-rate modems. In this work, to tune the maximum backoff time during the data collection mission, an adaptive mechanism has been implemented. Specifically, the maximum backoff time is updated based on the network density. This adaptive mechanism results in an 8% improvement of the network throughput.

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Cost-Effective Air Quality Monitoring System Based on an Open-Source Electronics Platform for Three-Dimensional Atmospheric Environmental Data Collection

10.5194/egusphere-egu2020-8307 ◽

2020 ◽

Author(s):

Yi-Chung Tung ◽

Dao-Ming Chang ◽

Chuang-Yuan Kuo

Keyword(s):

Air Quality ◽

Data Collection ◽

Open Source ◽

Monitoring System ◽

Three Dimensional ◽

Cost Effective ◽

Environmental Data ◽

Quality Monitoring ◽

Air Quality Monitoring ◽

Spatiotemporal Resolution

<p>Air pollution and extreme weather patterns have become serious issues over the world, especially in highly urbanized areas. &#160;In order to detailed study the atmospheric environmental change, the capability to perform high spatiotemporal resolution atmospheric environmental data collection is highly desired.&#160; In this research, we develop a cost-effective air quality monitoring system based on as open-source electronics platform (Arduino Uno Rev3) with multiple environmental sensing modules including particulate matter (PM) concentration, temperature, humidity, and sound sensors.&#160; An integrated monitoring system with one weather station (precipitation and wind sensors) and two sets of environmental sensors set up in different heights from the ground costs less than USD$300.&#160; The entire system is powered by a battery for portability, and all the data can be stored in a secure digital (SD) memory card for long-term monitoring. The cost-effectiveness makes it feasible for large-scale field tests with three-dimensional (3D) spatial resolution.&#160; In the experiments, the system is tested in urban areas, and the data collection performance has been confirmed.&#160; The results show that the data with single minute resolution can be successfully achieved in real-world scenarios with high air temperature (> 38<sup>o</sup>C) and rain conditions for more than 65 hours with a single-time battery setup.&#160; In addition, the data collected from different heights have shown distinct atmospheric environmental patterns suggesting that it is critical to perform 3D high spatiotemporal measurement and modeling for city-scale studies.</p>

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New Capabilities of EvoBot: A Modular, Open-Source Liquid-Handling Robot

SLAS TECHNOLOGY Translating Life Sciences Innovation ◽

10.1177/2472630316689285 ◽

2017 ◽

Vol 22 (5) ◽

pp. 500-506 ◽

Cited By ~ 5

Author(s):

Farzad Nejatimoharrami ◽

Andres Faina ◽

Kasper Stoy

Keyword(s):

Open Source ◽

Open Source Software ◽

Low Cost ◽

Integrated Analysis ◽

Experiment Data ◽

Time Interaction ◽

Modeling Software ◽

Offline Processing ◽

Liquid Handling Robot

We introduce a robot developed to perform feedback-based experiments, such as droplet experiments, a common type of experiments in artificial chemical life research. These experiments are particularly well suited for automation because they often stretch over long periods of time, possibly hours, and often require that the human takes action in response to observed events such as changes in droplet size, count, shape, or clustering or declustering of multiple droplets. Our robot is designed to monitor long-term experiments and, based on the feedback from the experiment, interact with it. The combination of precise automation, accurately collected experiment data, and integrated analysis and modeling software makes real-time interaction with the experiment feasible, as opposed to traditional offline processing of experiments. Last but not least, we believe the low cost of our platform can promote artificial life research. Furthermore, prevalently, findings from an experiment will inspire redesign for novel experiments. In addition, the robot’s open-source software enables easy modification of experiments. We will cover two case studies for application of our robot in feedback-based experiments and demonstrate how our robot can not only automate these experiments, collect data, and interact with the experiments intelligently but also enable chemists to perform formerly infeasible experiments.

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STUDI FENOMENA MENJEMUR PAKAIAN YANG MEMBENTUK CITRA KURANG BAIK BANGUNAN RUMAH SUSUN

Jurnal Koridor ◽

10.32734/koridor.v8i2.1341 ◽

2017 ◽

Vol 8 (2) ◽

pp. 144-148

Author(s):

Nurul Sucya Karya

Keyword(s):

Data Collection ◽

Low Cost ◽

Building Design ◽

The Sun ◽

Occupant Behaviour ◽

Top Down ◽

Collection Method ◽

Good Image ◽

Building Form

Menjemur is literally means drying laundry by hanging them to be exposed by the sun or open air. In Indonesia, misplaced menjemur phenomenon is frequently seen in low-cost apartment, which is giving a bad image to the building. By choosing the case of low-cost apartment (Rumah Susun) in Sarijadi Bandung, this small research tried to dig deeper towards misplaced menjemur phenomenon in Rumah Susun. The data collection method used for this small research is field observation and interview to the Rumah Susun occupants, which are then being analyzed descriptively. It can be seen that the Rumah Susun occupants improperly place their laundry to be dried, such as in balconies, corridors, stairs, and windows. This thing happened because there isn't any facility to place their laundry in Rumah Susun provided. Moreover, this phenomenon shows that the occupants don't have any other choice towards their settlement, which is called "bounded choice", as the result of Rumah Susun building programme orientation which is done by top-down method that produce a nearly uniformed building form. This bounded choice phenomenon could harm the Rumah Susun image, and in long term could reduce the occupants interest to live in Rumah Susun. An occupant behaviour-based improvement towards the Rumah Susun building programme is needed in the future, to produce a Rumah Susun form which has a good image. The outcome of this research could be a material to evaluate the Rumah Susun building design.

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Design of a Low-Cost Open-Source Underwater Glider

10.31224/osf.io/kvqmh ◽

2018 ◽

Cited By ~ 2

Author(s):

Alexander Williams

Keyword(s):

Data Collection ◽

Open Source ◽

Low Cost ◽

Center Of Mass ◽

Continuous Operation ◽

Use Case ◽

Underwater Glider ◽

Underwater Gliders ◽

Price Point ◽

3D Printed

Typical buoyancy engine-based Underwater Gliders are highly-complex and cost-prohibitive, generally ranging in price-point from 50,000USD to 250,000USD. A low-cost, Open-Source Underwater Glider (OSUG) was thus developed as a low-cost data-collection and research tool. This glider, OSUG, is a sub-1000USD, 1.2m long, 12kg, and capable of 50-hours of continuous operation. Its efficiency, and use-case feasibility were evaluated. The buoyancy engine is constructed of medical grade syringes that pull in water from the environment to simplify the system and lower costs. Direction of locomotion is controlled by altering pitch and roll via changing the center-of-mass. The system was designed to be primarily three-dimensionally (3D) printed and fully-modular to limit cost and ensure reproducibility.

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Low Cost and Flexible UAV Deployment of Sensors

10.20944/preprints201608.0180.v1 ◽

2016 ◽

Author(s):

Lars Yndal Sørensen ◽

Lars Toft Jacobsen ◽

John Paulin Hansen

Keyword(s):

Data Collection ◽

Open Source ◽

Low Cost ◽

Unmanned Aircraft ◽

Android Application ◽

Data Visualisation ◽

Time Data ◽

Ground Field ◽

Total Cost ◽

Sensor Applications

This paper present a platform for airborne sensor applications using low-cost, open-source components carried by an easy-to-fly unmanned aircraft vehicle (UAV). The system, available in open-source [1], is designed for researchers, students and makers for a broad range of their exploration and data-collection needs. The main contribution is the extensible architecture for modularized airborne sensor deployment and real-time data visualisation. Our open-source Android application provides data collection, flight path definition and map tools. Total cost of the system is below 800 dollars. The flexibility of the system are illustrated by mapping the location of Bluetooth beacons (iBeacons) on a ground field and by measuring water temperatures in a lake.

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baRcodeR with PyTrackDat: Open-source labelling and tracking of biological samples for repeatable science

10.1101/457051 ◽

2018 ◽

Cited By ~ 1

Author(s):

Yihan Wu ◽

David R. Lougheed ◽

Stephen C. Lougheed ◽

Kristy Moniz ◽

Virginia K. Walker ◽

...

Keyword(s):

Data Collection ◽

Open Source ◽

Biological Samples ◽

Low Cost ◽

R Package ◽

Biological Data ◽

Human Errors ◽

Field Samples ◽

Sample Management ◽

Globally Distributed

AbstractRepeatable experiments with accurate data collection and reproducible analyses are fundamental to the scientific method but may be difficult to achieve in practice. Several flexible, open-source tools developed for the R and Python coding environments aid the reproducibility of data wrangling and analysis in scientific research. In contrast, analogous tools are generally lacking for earlier stages, such as systematic labelling and processing of field samples with hierarchical structure (e.g. time points of individuals from multiple lines or populations) or curating heterogenous data collected by different researchers over several years. Such tools are critical for modern research given trends toward globally distributed collaborators using higher-throughput technologies. As a step toward improving repeatability of methods for the collection of biological samples, and curation of biological data, we introduce the R package baRcodeR and the PyTrackDat pipeline in Python. The baRcodeR package provides tools for generating biologically informative, hierarchical labels with digitally encoded 2D barcodes that can be printed and scanned using low-cost commercial hardware. The PyTrackDat pipeline integrates with baRcodeR output to build a web interface for sample management and tracking along with data collection and curation. We briefly describe the application of principles from baRcodeR and PyTrackDat in three large research projects, which demonstrate their value to (i) help document sampling methods, (ii) facilitate collaboration and (iii) reduce opportunities for human errors and omissions that could otherwise propagate through downstream data analysis to compromise biological inference.

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