Sensor Data Logging
Sensor Data Logging - Related Videos
08:36
Real-time Flight Control: Embedded Sensor Calibration and Data Acquisition
0 Views •
2023
Source: Ella M. Atkins, Department of Aerospace Engineering, University of Michigan, Ann Arbor, MI Overview Autopilot allows aircraft to be stabilized using data collected from onboard sensors that measure the aircraft’s orientation, angular velocity, and airspeed. These quantities can be adjusted by the autopilot so that the aircraft automatically follows a flight plan from launch (takeoff) through recovery (landing). Similar sensor data is collected to control all types of aircraft, from...
07:12
Façade-Level Monitoring of CO2 Variability under Urban Heat Island Conditions using Low-Cost Sensor Data Loggers
0 Views •
2025
A simple, effective environmental monitoring protocol to measure temperature, humidity, wind speed, and carbon dioxide variations across urban surfaces with differing sunlight exposure influenced by the urban heat island effect.
01:19
The Mantel-Cox Log-Rank Test
0 Views •
2025
The Mantel-Cox log-rank test is a widely used statistical method for comparing the survival distributions of two groups. It tests whether a statistically significant difference exists in survival times between the groups without assuming a specific distribution for the survival data, making it a non-parametric test. This flexibility makes the log-rank test particularly valuable in medical research and other fields where the timing of an event, such as death or disease recurrence, is of interest.
09:14
Glovebox and Impurity Sensors
0 Views •
2023
Source: Tamara M. Powers, Department of Chemistry, Texas A&M University The glovebox provides a straightforward means to handle air- and moisture-sensitive solids and liquids. The glovebox is what it sounds like: a box with gloves attached to one or more sides, which allows the user to perform manipulations within the glovebox under an inert atmosphere. For manipulations under inert atmospheres, chemists can choose between Schlenk or high-vacuum techniques and a glovebox. Schlenk and...
09:30
Bacterial Detection & Identification Using Electrochemical Sensors
0 Views •
Cited by 6 •
2013
We describe an electrochemical sensor assay method for rapid bacterial detection and identification. The assay involves a sensor array functionalized with DNA oligonucleotide capture probes for ribosomal RNA (rRNA) species-specific sequences. Sandwich hybridization of target rRNA with the capture probe and a horseradish peroxidase-linked DNA oligonucleotide detector probe produces a measurable amperometric current.
FAQs
The sampling interval determines how often a changing variable is represented in the record. Shorter intervals produce more closely spaced measurements, while longer intervals provide a less detailed sequence of values. Researchers should select an interval that matches the biological or environmental change they want to examine, because the choice influences how clearly patterns and responses appear during analysis.
Time stamps place each sensor reading within a defined sequence, allowing researchers to relate measurements to changes occurring during an experiment or field observation. This temporal organization supports comparison of conditions at different moments and helps reveal how organismal activity or environmental variables change over time. Without that ordering, interpreting patterns across a monitoring period becomes more difficult.
The measured variable determines what kind of biological or environmental condition enters the record. Sensors can represent factors such as temperature, light intensity, humidity, pressure, or movement as electrical signals for logging. Selecting a sensor that corresponds to the research question allows the stored measurements to describe the condition relevant to organismal activity, laboratory treatments, or field observations.
A study design should identify the variable to monitor, choose a corresponding sensor, and set the interval for collecting measurements. Researchers also need a way to store the values and later retrieve or transmit the record. These decisions determine whether the resulting data can support the planned analysis of changing conditions, biological responses, or treatment differences.
The approach is useful when researchers need a record of conditions or activity across an observation period rather than isolated measurements. In laboratories, it can track variables during experiments; in the field, it can document environmental conditions associated with organisms. The resulting record helps relate biological processes to changing surroundings and supports analysis after measurements have been collected.
A time-organized record allows researchers to examine how measured variables differ among treatments or environmental conditions. They can identify patterns in the stored values, quantify changes, and relate those changes to biological responses. This makes the records useful for comparing experimental groups, assessing organismal activity, and determining how changing conditions correspond with observed outcomes.