Questions related to Sensors
Description: I am working on a project with several IOT devices such as IP cameras and sensors, and I want to test its performance over a network. For this I am using NetSim simulator with emulation module. Can you let me know how to configure this? Thank you
Under what circumstances/application does one use Laser Vibrometer (which works under the principle of Doppler effect), Laser Triangulation Method and Laser Confocal Sensor. How does one determine which one is the best for a specifica application ? Also what is the difference when considering time to take one vibration measurement.
I am trying to explore data collection methods and protocols for transferring sensor data from the IoT devices to a local server.
Experimental here i mean purely laboratory experimental trial , e.g A sensor is designed in a laboratory and the functionality verified using artificial sample . what risk of bias tool can be used for such a study ?
I'm trying to find a solution for a problem related to satellote temperature data.
I work with intertidal environment, and I have temperature sensores deployed in these environment for years. Data shows the temperature observed by these in situ sensors are quite diferent from the satellite.
The problem is, I intend to do mechanistic species distribution models, but my mechanistic data was based on data colected by the in situ sensors, and these only exist on a few places, whereas the satellite data is everywhere.
Assuming, my in situ sensors are the 'correct ones', is there a way to calibrate the satellite data for the places where I have no sensors according to the diferences observed between satellite and in situ sensors in the places I do have sensors?
Cheers, Luís Pereira.
Hello, I hope the readers find this question well. I would like to know about how can i find line pressure specification of a pressure sensor (Sensor brand that i want to use is Pressure sensor, but another example would be okay). I have some difficulty on finding the value of line pressure. Thank you for your help.
how can we differ shrimp and other objects in pond with sensors.
like Kinect Sensor which is used for humans i need it for shrimps in turbid water
What is the role of sensors in precision agriculture and components of IoT based agriculture monitoring system?
With this question, I am asking for volunteer assistance with an open-source project, LoRaBinaryFloodMessaging within https://github.com/SoothingMist/Scalable-Point-to-Point-LoRa-Sensor-Network/tree/main. Allow me to explain.
Many applications, including precision irrigation, require remote sensing of data generated by various pieces of equipment. The project at hand uses LoRa point-to-point flood messaging to accomplish data transfer. The complexities and costs of LoRaWAN and third-party services are avoided.
The present project phase accommodates cameras and single-value sensors. At issue is that the GUI accommodates only one camera and one sensor. What is needed is an improvement to the GUI so that cameras and sensors are selectable. Was thinking that drop-down lists would do well. However, front-end work is not my specialty. What I have found so far on this topic confuses me.
The GUI is driven by a basestation written in Python. Matplotlib is used to create and continuously update the GUI's two plots. The camera plot is not a picture really, just the display of a numpy matrix that is updated as image segments arrive. How would I add drop-down lists to the GUI? An example of the present state of the GUI is shown in the attached jpg. More detail is in the project’s documentation. Glad for any comments, suggestions, or direct help. Many thanks for your input.
Is precision agriculture also known as satellite farming and what are IoT sensors used in precision agriculture?
Assume a mobile air pollution monitoring strategy using a network of sensors that move around the city, specifically a network of sensors that quantify PM2.5 at a height of 1.5 meters that lasts about 20 minutes. Clearly, using this strategy we would lose temporal resolution to gain spatial resolution.
If we would like to perform spatial interpolation to "fill" the empty spaces, what would you recommend? What do you think about it? What would be your approximations?
Which are the sensors can be used in agriculture in IoT and use of sensors in the field of automation and control?
What are the different types of sensors used in agriculture and application of sensors in the field of agriculture?
How are advanced fire safety technologies, such as early warning systems, intelligent suppression systems, and real-time data analytics, revolutionizing fire prevention, detection, and response in high-rise buildings and critical infrastructure, and what are the key challenges in integrating these technologies to ensure comprehensive and adequate fire safety measures?
Automotive manufacturers are increasingly utilizing artificial intelligence (AI) and machine learning techniques to enhance vehicle autonomy, safety, and overall driving experience in modern advanced driver assistance systems (ADAS) and autonomous vehicles. These technologies are revolutionizing the automotive industry by enabling vehicles to perceive their surroundings, make informed decisions, and interact with the environment more effectively. Here's how AI and machine learning are being utilized:
- Sensor Fusion and Perception: AI algorithms integrate data from various sensors, such as cameras, LiDAR (Light Detection and Ranging), radar, and ultrasonic sensors, to create a comprehensive and accurate perception of the vehicle's surroundings. Machine learning enables the system to learn and adapt to different driving scenarios, improving the accuracy of object detection, lane detection, and obstacle recognition.
- Autonomous Navigation and Path Planning: AI-based path planning algorithms use real-time sensor data and digital maps to plan safe and efficient routes for autonomous vehicles. Machine learning enables the system to consider dynamic factors like traffic conditions, road closures, and pedestrian behavior, ensuring smooth and safe navigation.
- Predictive Maintenance: AI and machine learning are used to analyze vehicle data to predict component failures and perform proactive maintenance, reducing downtime and enhancing vehicle reliability.
- Driver Monitoring and Behavior Analysis: AI-powered cameras and sensors inside the vehicle can monitor driver behavior, attention, and alertness. Machine learning algorithms can detect signs of drowsiness, distraction, or impairment, providing alerts or interventions to improve safety.
- Adaptive Cruise Control (ACC): AI is utilized in ACC systems to maintain a safe distance from the vehicle ahead. Machine learning models continuously learn and adapt to the driver's preferences and driving style.
- Lane Keeping and Lane Departure Warning: AI-based lane detection algorithms enable vehicles to stay within the lane, and machine learning helps in distinguishing intentional lane changes from unintended lane departures, triggering appropriate warnings if necessary.
- Advanced Collision Avoidance Systems: AI and machine learning techniques power advanced collision avoidance systems, which can autonomously apply brakes or take evasive maneuvers to prevent or mitigate collisions.
- Natural Language Processing (NLP) and Voice Commands: AI-powered NLP enables voice-based interaction with infotainment systems, navigation, and other in-car functionalities, improving the overall driving experience and reducing driver distractions.
- Data Security and Cybersecurity: AI is utilized to detect anomalies in-vehicle data and identify potential cybersecurity threats, protecting connected vehicles from cyber-attacks.
- Continuous Improvement and Over-the-Air Updates: AI-driven analytics enable automotive manufacturers to gather data from the vehicle fleet, monitor performance, and push over-the-air updates to improve algorithms, enhance features, and address safety concerns.
As AI and machine learning continue to evolve, automotive manufacturers will leverage these technologies to make autonomous driving safer, more reliable, and accessible to a broader range of vehicles, leading to transformative advancements in the automotive industry.
Nowadays, multiple areas of engineering use ultrasonic sensors, mainly due to their high precision within short distances and their robustness to electromagnetic interference. The well-known HC SR04 ultrasonic sensor generates ultrasonic waves at 40kHz frequency. While there is no shortage of information about its working principle, applications, and limitations, little is known about the energy density (i.e., intensity) of t ultrasonic pulses it generates. Could anyone provide me with such information? I will very much appreciate it!
We have designed a 2D photonic crystal sensor using optiFDTD software and we want to find the different resonance wavelength by changing the analytes or samples at the center of the 2D photonic crystal structure, using the observation point at the output end. When we change the samples, resonance wavelength does not change. so what to do ?
Can anyone explain please.
Literatures suggest that unlike non-ferromagnetic materials that lead to a decrease in impedance of the eddy current sensor, ferromagnetic materials lead to an increase in impedance of the coil. It is stated that this behavior is reversed at sensor frequencies > 1 MHz. Is it true?
1. In the practice of structural dynamics and control, non-minimum phase systems are common, and for the needs of motion and vibration control, we sometimes have to find a minimum phase one close to it. We can do this using structure modification、parameter adjustment, sensor position re-allocation, parallel compensator, series filter, output reconstruction, etc.
2. There seems to be a "critical" sytems in practice, for example, when adjusting the sensor position, when the sensor approaches the direction of the actuator, there will be a critical position, and when it approaches near, we obtain a minimum phase system.
3. Can we construct the concept of "the closest least phase system of the non-minimum phase system", just like the concept of "the closest linear system of the nonlinear system".
4. It is guessed that such a "closest least phase system" should (1) have a steady-state response and low-frequency response that is consistent or close to the original non-minimum phase system under closed loop; (2) Its inverse is a potential feed-forward controller of the original system; (3) Only minimal parameter adjustment is required; (4) Only minimum control effort is required.
5. If we could construct one somehow, it should be useful in theory and practice, at least, in the field of high-speed and high-precision motion control where I am interested in.
I am working on a project with sensors which are able to measure agricultural levels of nitrogen/potassium/phosphor, but also moisture/temperature/ph level. The sensor measures in mg/kg but the farmers we are trying to help need it in kg/hectare. We got the following formula to convert but the outcome is not right, I do think I know why but not how to solve it.
Nitrogen in kg/hectare= (mg N/kg x depth of measurement in CM x density of the soil in G/cm3)/10
I think the outcome is not perfectly right because of the depth of measurement. Normal with hand tests which are sent to the lab, the depth of measurement is more accurate and matters more. But I do not have a clue how to correct the formule, does anyone have experience in this field and know how to fix this?
Thank you for reading.
Morris la Crois
I require assistance regarding this issue:
How does a change in length of an optical tapered fiber impact the interference between different modes? If an optical fiber sensor relies on mode interference, how does the sensor's performance change with variations in the tapered fiber's length? Are there any relevant formulas to address this concern?
keywords: taper, optical fiber, propagating modes, optical fiber sensors
Currently I am working on SPR-PCF biosensor for biochemical detection , i am stuck in comsol multiphysics to find the sensitivity of SPR-PCF sensor how to do the analysis where to put the formula and how to check the results in comsol please someone suggest me the solution and please give the detailed explaination for that
I receive the received signal using an unmodulated continuous wave radar sensor and I'm struggling to obtain the relative distance of the object. I receive the IQ data in milli-volts and use the formula delta_phase = arctan2(Q_samples/I_samples), but the change in the phase as I plot is not that big although I keep on moving my hand back and forth from the sensor as I should see larger changes. The sensor is 61GHz and the wavelength is 4.92 mm. Any suggestion if I'm using the data in a wrong way or should I apply filtering before obtaining the phase change ??
Does anyone know of a fluorescent protein with an emission max greater than 720 nm? Which is the best fluorescent protein with an emission max greater than 700 nm for making a BRET sensor? I have many luciferase mutants which could serve as donors in the 610-630 range provided I find a good acceptor FP in the far red range.
Disposable medical sensors are easy-to-use and economical. Medical sensors, under which disposable medical sensors fall, are devices that aid in the detection of physical, biological, and chemical signals.
These devices offer a way for these signals to be recorded and measured.
I've done research on that, but I haven't found any suitable sensors to use. Please help me
When we receive the output of the sensor through the photodiode on the oscilloscope, it is in volts per pascal (sound pressure applied to the sensor), but to remove noises, etc., we need to convert this characteristic of the sensor into phase sensitivity.
How to convert mV/Pa to rad/Pa in the sensitivity of optical fiber sensors?
i have tested a structure using accelerometer sensors, the data is attached herewith,
can you please check the data and please help me to find the actual sensor data from the recorded data.
The manufacturer states the noise spectral density as 45 micro g /(Hz)^0.5.
Can you suggest a filter to denoise the data?
the sampling rate is 100Hz
I need to cure large number of PDMS based samples for the fabrication of piezoresistive sensors. But I do not have hot air oven for this purpose. What are the other option to cure PDMS other then keeping it at room temperature for 48 hours?
As we know that the smaller the cell size of an imaging sensor (CCD array) the lower the amount of light that reaches the cells of the sensor. However, the state-of-the-art sensors' cell size has already reached the smallest level. Does this fact lead to the poor contrast quality of an image acquired with the imaging sensors?
I am currently working on a project called double rotary inverted pendulum that requires the use of sensors for accurate measurement with minimal delay and noise interference. I have come across two types of sensors, namely the analogue Hall Effect Potentiometer Angle Encoder Sensor and the digital Rotary Incremental Encoder.
In the context of accuracy, delay, and noise levels, I would greatly appreciate expert insight on which of these two sensors is more suitable for my project. Can someone provide guidance on the pros and cons of each sensor type in terms of accuracy, delay, and noise reduction?
So we are given this problem:
A pressure sensor is specified to operate in the range of 0-100psia and provide a 4-20mA current loop output over this range. The pressure sensor current output is connected in the following configuration:
The load resistor used was measured as RL = 250Ω (±0.01%), and the resultant voltage VL was measured with an ADC with an error of ±0.5% FSO (10VDC).
Given that I have an equation:
P = 6250(V/R) - 25
That where I ask my question...
When simulating a wireless sensor network in NetSim, what are the parameters to vary to increase/decrease the communication range of the sensors? How is the default range calculated? How can I modify the GUI grid size (environment) in proportion to the communication range?
How can we use sensors and other IoT devices to collect real-time data on soil moisture, temperature, and other environmental factors that affect crop growth?
Early leak detection in an offshore hydrocarbon pipeline is critical for ensuring the safety of personnel and the environment. However, it is challenging to achieve effective leak detection without false alarms, as a variety of factors can cause false alarms, such as changes in temperature, pressure, or flow rates, as well as instrument malfunction or even marine life interference.
Several technologies are available for early leak detection in offshore pipelines, including acoustic, thermal, and optical sensors, among others. Each technology has its strengths and limitations, and the most effective solution may depend on various factors, such as the pipeline location, operating conditions, and type of hydrocarbon being transported.
One approach to minimizing false alarms is to use multiple sensors and incorporate them into a comprehensive leak detection system that can analyze data from different sensors and cross-check the results to reduce false alarms. Additionally, regularly testing and maintaining the sensors and system can also help to minimize false alarms and ensure that the system is functioning effectively.
Ultimately, achieving effective early leak detection without false alarms in offshore hydrocarbon pipelines requires a combination of appropriate technology selection, system design, and regular maintenance and testing to ensure optimal performance.
Please elaborate on your opinion on it.
Generally, experimentalists apply thermal effects (temperature) to determine the recovery time of a sensor, which can theoretically be determined through transition state theory by the following equation: 📷 Here v, Eads, K and T are the attempt frequency, adsorption energy, Boltzmann constant and temperature, respectively.
How the attempt frequency of any material used as a sensor can be calculated theoretically? As in the articles, they only mention the reported values 10^-10 or 10^-12. Is this value constant?
I am working with high-frequency (144 measurements/day) temperature logger data. It was two individual temp loggers measuring at equal intervals (10 mins) at the same stationary location for 120 days.
One sensor was calibrated, while the other was not. The uncalibrated sensor shows high drift after about a month of use. I am looking to determine the statistical significance between between the logger types (calibrated vs. uncalibrated).
I was wondering if there was a way to compare the mean daily values of loggers (calibrated vs. uncalibrated) and then determine at approximately what day did the daily means become statistical different (i.e. day 24 of 120).
To start, I was thinking of using a paired t-test. However, the data (>10,000 points for each dataset) are non-parametric. I am thinking with the large sample sizes a paired t-test will be sufficient.
Any and all advice is greatly appreciated!
Hello all, I am looking to simulate a heterogeneous Wireless Sensor Network (WSN) with energy harvesting devices for my research. The network should consist of at least two classes of wireless sensors: a set of low-energy normal sensors and another set of overlay sensors, which could be high-energy or preferably energy harvesting sensors. The data collected by these sensors should be transmitted to an external fusion node. My goal is to vary properties such as clustering and study network performance and lifetime. Currently, I am using the NetSim simulator, but I welcome directions on using any other simulator as well.
As technology advances, cables and classic electrodes will disappear, AI and sensors will take hold instead. New monitoring devices will have to be developed, they will be less invasive, smaller, more comfortable and performing in the same way.
Optical tweezers (OT) is a well tool for many research fields, especially in biology and physics, which can be used to manipulate tiny objects, measure weak forces, and sensor a local area. But, it seems not to be used in industry yet. So, my question is what the future of OT is.
Which temperature sensor is widely used and what do you understand by vertical and horizontal variation in temperature and how vertical temperature profiles obtained?
An IoT-based system uses ESP32, ESP8266, PZEM 004T, and other sensors, software, and smart devices to collect data on energy consumption, production, and distribution in a smart microgrid and process this data to provide a perception of energy use and optimize energy management.
For measuring the response time of SPR-based sensors, Is there any specific formula or theoretical explanation for that? Need some references.
By whole-body I mean a single dynamic measurement that contains the health measures for a bridge. Not, for example where multiple vibration sensors are placed at locations and their data reintegrated at a later date.
How can precision agriculture technologies, such as drones and sensors, be used to optimize crop yield and reduce input costs?
Hello, I am from Argentina and I am an electronic engineer and PhD student working with resonators. I have made several PDMS chips for microfluidics but I don't know how to stick/glue them to the sensor in a non-permanent way. Also, fluid should not spill on the sensor (only on the gold sensing area). For that reason the PDMS chip is made to guide the liquid.
I hope for an answer !
I am working on a small wind turbine as part of my internship for my course. The rated capacity of the small wind turbine is 700 watts at a rated wind speed of (…) m/s. The turbine is installed on a (height of the pole) m- steel pole/ tower. Further, the turbine is connected to the local electricity grid.
Challenges faced: At 3 m/s- windspeed, I am observing that the connected sensors/ electronics are consuming 15W
My research is the development of electrochemical sensors such as glucose, lactate, and potentiometric ion sensors based on Au electrodes.
Au electrodes in the electrochemical application have nano-structures for the large electro-chemical active area. Unfortunately, electrodeposition of sensing materials is not uniform on the surface, resulting in low reproducibility and sensing performance. In an attempt to address this issue, I employed the CV method under 0.25M HCl to clean the Au surface. However, this approach did not yield the desired results.
Therefore, I am seeking your expert advice on how to obtain reliable Au electrodes that can offer consistent and accurate results. I would greatly appreciate any suggestions or recommendations you may have to improve the reproducibility of these sensors.
I have fabricated an impedimetric aptasensor for small molecule detection. The black line in the attached Nyquist plot is the EIS measurement before incubation with the target. After incubating with the target for 1 hour, the EIS measurement gives a lower value of Rct was observed (purple line). The target incubated sensor is then washed with deionized water and dried in a nitrogen stream. The EIS measurement was again performed and a higher Rct was observed (red line). (all measurement was performed in 5 mM FerriFerro and 0.1 M KCl). The aptamer is linked with C6 and the sensor is unblocked) Anyone can explain this phenomenon?
I once thought about the possibility of predicting earthquakes by implanting a special sensor chip in mice. But then I thought more: If this sensor chip is always in the mouse's body, it will affect the normal ability of the mouse. So good results cannot be obtained from it. What do you think about it?
AI to recognize cardiac arrhythmias like by using thermoscanner and other physiological sensors. New way and new product without the classic electrodes.
I am going to desing an optical Fiber Bragg grating sensor for pressure and strain measurement using COMSOL software. But, I am new in this software so if anybody having any idea about this please help me out.
Thanks & regards
I have data from a vibrating specimen in one direction with an input of 1G sine sweep. There are accelerometers in different locations. All data from these sensors in FFT has 2 close peaks. It is due to two modes are close to each other in frequency. But other than than, I am wondering if we can get more information from these peaks.
I am working on a project on, force feedback system in a 3 finger barot gripper,For that i need CMC sensor for integration with gripper system.
I have collected muscle activity data with the Muscle Sensor v3 Kit. Now I would like to apply a machine learning algorithm to it. According to the datasheet for this sensor, it has already been amplified, rectified, and smoothed.
Would anyone be able to tell me if the data needs to be denoised before applying machine learning? Here's the data how it looks like after plotting.
Here's the data how it looks like after plotting:
I have a drive shaft connected to a torque sensor but to avoid damage I must constrict the linear motion to pure rotational motion of the shaft. Although the displacement of the shaft is a few millimeters, the force will be quite huge. How do I convert the linear and rotational motion of this shaft to pure rotational motion without sacrificing the torque output?
How to solve the problem if the sensor is not capable of transmitting data to base station in WSN. Is there any paper talking about this issue?
l want to develop a device that can detect animal action which denote a sign of illnesses and alert the owner for emergency check up of such animal.which sensor that are very sensitive for the work.
Let's have an FMCW radar sensor. I arrange the raw data in a matrix format with MXN dimensions, where M represents the number of time samples per chirp and N represents the total number of chirps. Now, after taking the FFT across each column, what do we get? Is it a range-time plot or a range doppler? I am confused after seeing many representations of the radar data plot. For example, range-time, range-doppler, time-doppler, and velocity-time plots. What are they, and how can I obtain each of them?
I’ve been racking my brain to try to figure out the image aberration balance method with unknown lens design data method, the optical sketch is shown below,the camera is put at the final image plane, the current final image is not so good. the problem is the there is an unknown design in this optics train, so I can neither adjust nor redesign the following components to balance the final image aberration. I come up with a method which is: i put an image aberration sensor at the first image plane, the sensor would read out the first image aberration in terms of Zernike coefficients, then I start a new design, i put a dummy surface which contains the first image aberration in terms of Zernike coefficients at the first image plane position. and then I can adjust or redesign the following components in this optical train. Do this method make sense?
What kind of strain gauge is optimal for a bridge subject to fatigue loads? I'm conducting my PhD dissertation and wanted to know. To purchase the sensors, I need particular technical information. Could someone offer assistance with this? I appreciate any help/suggestion.
I have a sensor with Ni nanoparticles on reduced graphene oxide for glycerol determination and need to calculate the thickness of the sensing membrane...
Is there any way to calculate based on theory or do I need to perform a TEM?
I am looking for some sensors to monitor environmental variables such as Soil moisture, temperature, relative humidity, light, wind and rainfall. I found some companies such as the HOBO dataloggers by ONSET, as well as another company called Renke from China that also produces such sensors for environment monitoring.
Are there any other brands that you know of? And it will be very helpful to let me know if those sensors are considered low cost or on the higher end of the budget.
Thank you everyone for your suggestions.