Live Pressure Mapping

€45-50 EUR

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€45-50 EUR

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Live Pressure Mapping — System Description and Requirements 1) Purpose and operating context The system is a live pressure-mapping solution intended to measure and visualize pressure distribution during induction-welding of thermoplastic composites. The intended operating envelope is a high-EMI induction environment (approximately 300–500 kHz field present) and a process context that can involve high temperatures (on the order of ~400 °C near the tool) and typical bonding pressures in the ~5–8 bar range. The software and filtering must be designed for robust performance under electrical noise and transient interference. 2) Sensor hardware Sensor type: Force Sensitive Resistors (FSR). Active sensing diameter: 26 mm (circular active area). Maximum force reference: 450 N. Truth constraint for scaling/normalization: The measurement system must uphold the calibration truth that the sensor output corresponds to ~3.00 V at 450 N (you sometimes accept 2.99 V, but the target is 3.00 V @ 450 N). Number of sensors: 16 FSRs, sampled as a set to produce a live “frame” of pressure values. 3) Signal conditioning and resistor network Voltage divider configuration: The FSR is used in a divider powered from the Pico’s 3.3 V rail. Fixed resistor value: 94 kΩ to ground (0 V) (this replaces the earlier 100 kΩ note). Measured node: The divider midpoint (FSR–resistor junction) is routed through a multiplexer into the Pico ADC. 4) Multiplexing topology Multiplexer: 16-channel analog multiplexer/demultiplexer, controlled by 4 select lines (typical CD74HC4067-style behavior). Enable behavior: The MUX EN pin is wired to “-” (ground), meaning the multiplexer is permanently enabled (active-low enable held low). Channel scanning: All 16 channels (commonly referred to as C0–C15) must be scanned cyclically to form each complete 16-sensor frame. 5) Microcontroller and pin mapping (fixed) MCU: Raspberry Pi Pico W, running MicroPython. ADC input (fixed): GP28 / ADC2 is used as the single analog measurement input. MUX select pins (fixed wiring): S0 → Pico physical pin 4 → GP2 S1 → Pico physical pin 5 → GP3 S2 → Pico physical pin 6 → GP4 S3 → Pico physical pin 7 → GP5 These select lines must be driven to address channels consistently and repeatably, and the mapping must remain stable so that pressing a specific sensor (e.g., “C3”) always affects the expected cell in the visual map. 6) Sampling, stability, and frame-rate requirements Target output rate: Approximately 20 Hz for a full 16-sensor frame (i.e., ~20 complete frames per second, not 20 samples on a single channel). Noise robustness: Because of the induction environment, the firmware must include stability measures such as: ADC averaging per channel read (and optionally median-based rejection of spikes). Smoothing that reduces jitter while remaining responsive to real pressure changes. The software must avoid “dead” channels and include a way to confirm channel responsiveness (especially to prevent recurrence of the issue where applying pressure to C3 does not change the output). 7) Required computations and units For each of the 16 channels, the system must produce values in multiple representations: Raw ADC reading (Pico ADC units). Voltage derived from ADC conversion. Force (N) derived from calibration. Pressure (bar) derived from force and sensor area. Pressure conversion must use the known FSR active area: Radius: 26 mm diameter → radius 13 mm = 0.013 m Area: A=π⋅(0.013)2 A=π⋅(0.013) 2 m² Pressure (Pa): P=F/A P=F/A Pressure (bar): Pbar=P/100000 P bar =P/100000 The visualization and analysis focus should prioritize 4–8 bar, but the conversion pipeline should remain valid across the usable range, including the upper force reference. 8) Calibration requirements (critical) The system must not fabricate calibration data. It must support per-sensor calibration (each of the 16 FSRs may have its own curve/coefficients). The system must support both: A measured interpretation (direct calibrated output). A scaled/normalized interpretation to correct for known recording inconsistencies, explicitly enforcing the constraint 3.00 V @ 450 N when normalization is applied. Calibration alignment must be based on meaningful ramp detection/behavior rather than naive timestamp matching when runs were recorded at different times (consistent with your earlier requirement that “it should fit based on where it sees significant change in the ramp up”). 9) Data output and interface requirements Pico-to-PC streaming: The Pico must stream the complete 16-channel frame in a structured, machine-readable format suitable for real-time parsing (CSV-line or compact JSON). No terminal spam: Output should not be verbose human debug text during operation; it should be structured data suitable for plotting/logging. Diagnostics mode: A clear diagnostic procedure must exist to validate: MUX selection is correct. Each channel responds when pressed. Example: a mode that isolates one channel (like C3) or reports min/max activity per channel over time. 10) PC-side live visualization and logging requirements The PC application must: Read the Pico’s stream from USB serial. Display a live 4×4 pressure heatmap representing the 16 sensors. Provide both views: Measured and Scaled/Normalized. Be visually clean and stable (not “messy”), with clear labeling/indexing so channel mapping is unambiguous. Logging: Save time-stamped data (time in seconds) and all 16 channels (at least pressure, and preferably also voltage and force) to CSV. Produce an Excel (.xlsx) output after a run or on demand containing raw logs and computed columns. 11) Success criteria The solution is considered correct when: A full 16-sensor frame updates at ~20 Hz reliably. Pressing any sensor (including C3) produces a clear, immediate, and correctly mapped response in the live heatmap. The conversion chain produces sensible values with a clear operating focus around 4–8 bar. Calibration handling includes both measured and scaled outputs and respects the 3.00 V @ 450 N constraint when normalization is enabled. The system remains stable and usable in a noisy induction-welding environment through averaging/filtering and diagnostic validation.

Electrical Engineering

Embedded Systems

Data Analysis

ID do Projeto: 40134663

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@tshibsamuel477

Hi there, I’ve carefully reviewed your flow and requirements, and I’m confident I can design a reliable motion-sensing controller that meets your ignition-powered, engine-off constraint. I have hands-on experience with NE555-based PWM generation, Hall-effect motion detection, MOSFET motor drivers, and robust 12 V automotive power regulation using devices like the 7805 with proper protection. I can deliver a clean schematic and wiring approach where the Hall sensor reliably detects steering rotation, gates the NE555 to generate adjustable-frequency PWM, and safely drives a high-torque 12 V motor via a suitable MOSFET. The design will include ignition-switched power-up behavior, motion timeout (motor off when no rotation is detected), and recommendations for frequency adjustment, filtering, and transient protection suitable for automotive environments. Feel free to message me so we can review the diagram details and move forward. Best regards, Samuel tshibangu

€75 EUR em 1 dia

5,0

(75 avaliações)

6,3

25 freelancers estão ofertando em média €64 EUR for esse trabalho

@AmazingEngr76386

With over 10 years of experience in the fields of Arduino, Electrical Engineering, and Data Analysis, your project is right up my alley. I have a mastery of Arduino and have worked extensively with data analysis tools like Pandas in Python which would be tremendously helpful for your project. I also understand the importance of clean and accurate data visualization as evident in my skill in your project needed handling the data force over voltage. Your request to have live graphs of bar vs time force vs time voltage vs time and resistance vs time is definitely possible and I'm well versed in this aspect. My approach to projects has always been hands-on; thus, I can assure you of direct and personal involvement at every stage of the process. You will not only benefit from my knowledge as an individual but also have access to my network of experts if the need arises. Furthermore, I believe long-term support and post-launch updates are integral to a successful completion. After delivering your project, I'll remain available for any issues that may arise or additional tweaks needed post-implementation. I'm excited about the potential collaboration on this unique real-time 16-FSR Logger project with you!'

€48 EUR em 7 dias

4,5

(33 avaliações)

6,6

@julianm260

Hi, Cloak. I have built multi-channel sensor logging systems using Raspberry Pi Pico, analog multiplexers (CD74HC4067), and Python, including a 16-channel FSR array logger sampling at 500 Hz with real-time plots, calibration curves (force vs voltage), and automated CSV/Excel export used successfully in lab testing with <2% measurement error. My approach will be: (1) implement synchronized mux channel cycling with deterministic timing on the Pico so all 16 FSRs appear as simultaneous streams, (2) perform pre-run calibration and polynomial/curve fitting (force–voltage–resistance) stored as calibration profiles, (3) stream calibrated data via USB to a CMD-based Python logger using NumPy/Pandas, and (4) render live plots of pressure (bar), force, voltage, and resistance vs time per channel using Matplotlib with clean channel labeling (C15–C0). I will ensure continuous logging without stop-restart by buffering ADC reads and timestamping each channel so the visualization feels real-time and non-multiplexed. Do you already have calibration datasets per FSR or should I generate a calibration routine, and what target sampling rate per channel do you need for accurate pressure mapping?

€45 EUR em 7 dias

5,0

(1 avaliação)

4,4

@redbrickamerica

Hello! We're proficient in Data Visualization, Python, and Electronics to develop a real-time 16-FSR logger for you. Our cmd log will cycle pins of the mux and pico to capture all 16 points simultaneously. We'll handle calibration, fitting data force over voltage, and provide live mapping of pressure in bar with graphs for bar, force, voltage, and resistance vs. time. Using Thonny, we'll ensure seamless distinction of C15 to C0 points. The project will utilize Pandas, NumPy, and Arduino for efficient data analysis and visualization. Ready to start immediately! How can we assist you further?

€45 EUR em 2 dias

5,0

(1 avaliação)

3,8

@jesica46

Hello there, As an experienced researcher and data scientist, data analyst, my qualitative analysis skills perfectly align with your job requirements. My profound knowledge of Python and R Studio guarantees fast learning and adaptation to new tools. Moreover, my advanced skills in Excel make me highly competent in handling large datasets efficiently—making me proficient in extracting the best insights from your transcripts. I fully comprehend the importance of working papers and meticulously preparing financial statements, especially within strict timelines. my sharp analytical skills and extensive knowledge of excel ensure that I leave no stone unturned in making sure every detail is covered under evaluation. My passion for quality, originality and meeting deadlines makes me an excellent choice for this project. I cannot wait to prove my extensive skills to you through providing actionable insights that will help guide your decision making regarding domestic charter flights. Best Regards

€45 EUR em 1 dia

4,3

(6 avaliações)

3,4

@ThynkLoop

Hi, I can deliver this end-to-end pressure-mapping system exactly as specified, focusing on reliability in a high-EMI induction-welding environment. I will handle both **Pico W firmware** and **PC-side visualization**. On the **firmware side (MicroPython)**: * Deterministic scanning of all 16 FSR channels via the fixed MUX pin mapping (GP2–GP5 → C0–C15). * Stable ~20 Hz full-frame output using per-channel averaging and spike rejection to handle induction noise. * Correct conversion pipeline: ADC → Voltage → Force → Pressure (bar), using the defined sensor area. * Per-sensor calibration support, plus an optional normalized mode enforcing **3.00 V @ 450 N** without fabricating data. * Diagnostic mode to verify channel responsiveness (e.g., isolate C3, min/max activity check). * Clean, structured USB serial streaming (CSV or compact JSON), no debug spam. On the **PC side**: * Live 4×4 heatmap with clear channel indexing. * Toggle between measured and normalized views. * Stable visualization (no jittery redraws). * Time-stamped CSV logging and Excel export with pressure, force, and voltage columns. Success criteria will be validated against your list: correct channel mapping, immediate response, usable 4–8 bar range, and stable operation under EMI. I can start with a channel-verification build first, then finalize calibration and visualization.

€48 EUR em 7 dias

5,0

(3 avaliações)

2,0

@eliza019

Hello there, With extensive experience in statistical and predictive analytics, My proficiency in SPSS combined with my programming skills in Python will not only ensure an effective data analysis but also allow for flexibility and automation, optimizing efficiency throughout the process. Throughout my career, I have consistently proven my problem-solving mindset transforming complex datasets into clear and actionable insights that clients can use to drive their business forward. Data cleaning and transformation is an often-overlooked area of importance; however, it's where precise analysis begins. My vast experience in this area ensures thorough sorting of your data for accurate analysis - leaving no stone unturned. Lastly, I recognize that clear communication is vital to successful project completion. I assure you of my commitment in communicating regularly and effectively throughout this project, leaving no room for ambiguities. Trusting me with this project will not just avail you of a qualified individual but also someone who is dedicated in leveraging their knowledge and experience for unparalleled client satisfaction.

€48 EUR em 1 dia

5,0

(1 avaliação)

1,4

@novatech2210

Hi Cloak, Just wrapped up a live pressure-mapping system for a thermoplastic composite manufacturer – a high-EMI, high-temperature environment with multiple FSR sensors, robust ADC averaging, and a stable Raspberry Pi Pico W microcontroller. This project shares similar system requirements with yours, including 16-channel sampling, calibration validation, and live visualization. We’re the perfect fit for this project. I specialize in building reliable sensor systems using Python, MicroPython, and advanced signal processing techniques. My expertise includes structured data acquisition, filtering, and real-time visualization. Multiple 5-star reviews on complex industrial automation and sensor systems. I'd be happy to discuss your specific needs and provide a free consultation, even if you decide not to proceed with the project. Chris | Lead Developer | Novatech

€47 EUR em 14 dias

1,0

(2 avaliações)

1,9

@QuickMentor

Real-Time 16-FSR Logger I’m an experienced Full Stack Developer skilled in JavaScript (React, Node.js, Angular), Python (Django, Flask), PHP (Laravel, WordPress), and mobile frameworks like Flutter. I build high-performing, scalable, and fully responsive web and mobile applications tailored to your business needs. I ensure clean, efficient code and timely delivery. To kick things off, I also offer a free initial consultation to fully understand your project requirements. Let’s discuss your project today and start building a solution that exceeds your expectations!

€45 EUR em 1 dia

0,0

(0 avaliações)

0,0

@Jacobkim89

Greetings, Having carefully reviewed your project description, I am confident in my ability to execute this project to perfection. I possess a broad spectrum of skills, knowledge, and experience in this specific field, making me the ideal candidate to handle your project. My proficiency includesElectronics, Data Analysis, Pandas, Embedded Systems, NumPy, Python, Electrical Engineering, Data Visualization, Raspberry Pi and Arduino, which positions me as the best choice for the successful completion of your project. While I am well-prepared to begin, I have a few clarifying questions. Kindly drop me a message in the chat so that we can engage in a discussion regarding the project's budget and deadline. Thank you, and I look forward to the opportunity to collaborate on your project.

€150 EUR em 3 dias

0,0

(0 avaliações)

2,3

@josephw159

Hi there, I’ve reviewed Real-Time 16-FSR Logger and your goal of live, calibrated, 16-channel mapping with a mux and Pico, plus live graphs of bar, force, voltage, and resistance over time. I’ve spent 13+ years as a Senior Software Architect building embedded data-acquisition and analytics for sensors, with Python, NumPy, Pandas, and data visualization, and experience with Arduino/Raspberry Pi ecosystems. For your project, I would architect a synchronized 16-channel sampling flow using a mux (C15 to C0) controlled by the Pico/RPi, loading per-channel calibration files to map raw readings to pressure (bar), resistance, and force. Data would be streamed to a local log (CSV/SQLite) and exposed to live plots (Matplotlib/Plotly) with real-time updates and an export-to-Excel option. The solution would ensure near-simultaneous sampling, deterministic timing, robust error handling, and easy calibration updates. A minimal viable milestone can be delivered quickly to validate the pipeline, followed by enhanced visualization and export features. If this aligns with what you’re looking for, I can start with a short technical discussion or a small milestone to validate the approach. Best regards,

€45 EUR em 6 dias

0,0

(0 avaliações)

0,0

@mohit8k

Hi there, I understand exactly what you are trying to achieve—moving away from the manual "stop-start" logging in Thonny to a proper real-time data acquisition system. I can build a Python solution that rapidly cycles your Multiplexer pins to read C0 through C15 in a tight loop, creating the effect of simultaneous data capture. On the PC side, I will create a script that takes this raw stream, applies your specific Force/Voltage calibration in real-time, and generates the four live subplots you need (Bar, Force, Voltage, and Resistance vs. Time). This will completely automate the process, allowing you to see the live pressure mapping without ever needing to touch the code during the test.

€48 EUR em 7 dias

0,0

(0 avaliações)

0,0

@tetianam8

⭐⭐⭐⭐⭐ Yes — this is absolutely possible, and your description is very clear. I’ve done very similar multi-channel sensor logging and calibration work with Pico + MUX + FSRs. Here’s how I’d approach it: • Configure the MUX so channels C0–C15 are scanned fast enough to appear simultaneous (interleaved sampling with timestamps). • Build a single continuous logging loop that tags each ADC read with its channel ID, so all 16 points are always distinguishable in real time. • Implement a calibration phase first (force vs voltage curve fitting per sensor or shared model), store coefficients, then automatically switch to live mode. • Convert raw ADC → voltage → force → pressure (bar) on the fly using the calibrated fit. • Live plotting of bar, force, voltage, and resistance vs time per channel (either via Python matplotlib or streamed CSV for real-time dashboards). • Generate clean Excel/CSV output without stopping acquisition, unlike your current start/stop workflow in Thonny. Tooling: MicroPython or Pico SDK (depending on speed needs) Thonny-compatible workflow Structured CSV/Excel output with channel separation Optional real-time plots + post-run analysis End result: You’ll see 16 live pressure points updating continuously, with no visible “cycling,” and fully calibrated physical units. Happy to adapt this exactly to your Pico + MUX wiring. If you want, I can also make the calibration reusable across runs.

€48 EUR em 7 dias

0,0

(0 avaliações)

0,0

@habiba8730

Hi, I’m Mst Habiba Hasan, I am a Senior Full-Stack Developer with more than 10 years of experience. I can help you with: — Website development — Mobile app development — Web app development — Backend development — AI and Machine Learning development — Maintenance of existing projects — UX/UI design — Browser extensions — DevOps — Solution Architecture — Consulting — MVP development Technologies I've worked with include but are not limited to: • Python/ Django • ReactJS / React Native (including React Native Web) / Expo / Express / Redux / NextJS • Javascript / Typescript / Flow types • NodeJS / Angular / Vue.js • MongoDB / SQL (MySQL / MariaDB / PostgreSQL) / Redis • OAuth2 / Keycloak / Auth0 / Cognito • Kubernetes / Helm / Docker / Ansible / Terraform / Amplify / Firebase • AWS / Azure / GCP / on premises • RESTful / GraphQL / OpenTracing / AMQP (RabbitMQ) Contact me today to get started! I’m excited to collaborate and bring your vision to life. Best regards, Mst Habiba Hasan

€45 EUR em 7 dias

0,0

(0 avaliações)

0,0

@langstonc1

I can build a MicroPython-based logging system in Thonny for your Pico that handles a 16-channel MUX (C0–C15) while presenting the data as if all points are sampled simultaneously. I’ll implement a fast scan with proper timestamping so each FSR channel is clearly distinguished and mapped live. I’ll also integrate a calibration stage that fits force vs voltage, converts to pressure in bar, and applies that calibration during runtime. The system will generate live graphs for pressure, force, voltage, and resistance vs time, and export clean Excel/CSV logs without manual stop/start steps.

€50 EUR em 3 dias

0,0

(0 avaliações)

0,0

@stefanw71

I can redesign your current ADC logging workflow to support a 16-point MUX while keeping the experience “simultaneous” from the user side. Using the Pico and MicroPython, I’ll handle MUX pin cycling, channel tagging (C0–C15), and synchronized data capture. I’ll implement calibration handling (force over voltage curve fitting) and apply it live so pressure in bar is shown in real time. You’ll get continuous logging, live plots (bar, force, voltage, resistance vs time), and automatic Excel export without restarting the script.

€75 EUR em 2 dias

0,0

(0 avaliações)

0,0

@mekhig

I can create a complete data acquisition and visualization pipeline for your Pico + MUX + FSR setup. The code will scan all 16 MUX channels rapidly, label each channel clearly, and present them as parallel live signals. Calibration will be handled first (curve fitting force vs voltage), saved to files, and reused during measurement. During runtime, you’ll see real-time graphs of pressure (bar), force, voltage, and resistance vs time for all channels. Logging will be continuous and structured, producing Excel-ready outputs without manual intervention.

€55 EUR em 3 dias

0,0

(0 avaliações)

0,0

@shyams146

I can upgrade your current Thonny-based Pico logger into a multi-channel, calibrated measurement system using a 16-channel MUX. I’ll handle MUX selection logic, ADC reads, and timing so all 16 FSR points are distinguishable and appear live, not sequential from a user perspective. Calibration will convert raw ADC data into force and pressure (bar) using fitted curves. You’ll get live plotting of all required parameters and clean CSV/Excel logs generated automatically, removing the need to stop and restart logging.

€45 EUR em 5 dias

0,0

(0 avaliações)

0,0

@coliner1

I can develop a MicroPython solution for your Pico that treats a 16-channel MUX as a true multi-point sensor array. The system will scan C0–C15 efficiently, tag and buffer data, and display live readings for all FSRs simultaneously. I’ll implement a calibration routine that fits force vs voltage, stores calibration files, and applies them in real time to output pressure in bar. Live plots will include bar, force, voltage, and resistance vs time, and the logger will continuously generate structured Excel-compatible files.

€80 EUR em 2 dias

0,0

(0 avaliações)

0,0

@yaroslavmark

l✅Okay, I got what you want exactly. I am an embedded systems & data acquisition engineer with over 10 years of experience, providing Python-based logging, Raspberry Pi Pico firmware, analog sensor calibration, multiplexed ADC systems, and real-time data visualization. This project is very similar to my previous works. I’ve built a 24-channel pressure-mapping system using a Pico + CD74HC4067 where I handled per-channel calibration, oversampling, and live plotting at 50 Hz per sensor. I also developed a Python pipeline using NumPy and Pandas to export structured Excel logs while streaming live plots for voltage, resistance, and force simultaneously. ✅ So, I will divide your project like following: ⚡ Design fast MUX channel switching and synchronized ADC sampling on the Pico ⚡ Implement calibration fitting (force vs voltage) and channel-specific lookup files ⚡ Build real-time Python CMD logger with live multi-graph visualization ⚡ Export structured Excel logs with all 16 channels clearly labeled (C0–C15) Via private chatting or meeting, I will provide the creative idea and good tech solution for your project and I want to discuss about the budget and timeline in detail. Best regards. Yaroslav

€45 EUR em 7 dias

0,0

(0 avaliações)

0,0

@Isirmayor

Drawing from my extensive experience in systems engineering and test management, I am confident that I am the perfect fit for your Live Pressure Mapping project. With a background in both hardware/software integration and test automation, I have a solid understanding of the intricacies involved in building solutions for sensitive measurement systems like the one you need. My skills in Python programming are highly relevant to this project, as it requires precise calibration and data processing. I have utilized Python extensively for automated test pipelines and validation environments in the semiconductor industry where precision is paramount, much like in your 16 FSRs which may have their own curve/coefficients. This means I can create a system that ensures accurate measurements and reliable analysis that meet your unique needs. As an engineer who prioritizes robustness and scalability, I can assure you that the system I develop for you will be able to perform effectively even in high-EMI induction environments and withstand high temperatures without compromising functionality or data quality. In addition to my technical expertise, my attention to detail and commitment to delivering well-documented solutions align perfectly with your need for a system that does not fabricate calibration data but rather upholds calibration truth. Simply put, with me on board your project, you won't just get a system built; you'll get a sustainable solution built to last.

€88 EUR em 7 dias