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capacitive touch sensor  (Adafruit Industries)
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Custom Sensor design for liquid level sensing. The image shows the custom sensor design that has been implemented on a flexible printed circuit board (PCB) to measure the liquid level inside the bottle. The <t>FDC1004</t> chip has been placed on the board for capacitive liquid sensing and labeled as U1. Two pull-up resistors for I 2 C signals have been mounted on flexible PCB, whereas C3 and C4 are decoupling capacitance. The P2 has 4 male pins for power supply and the I 2 C signals.
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https://www.bioz.com/product/capacitance+sensors/pm41950926-208-11-15?v=Adafruit+Industries
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Custom Sensor design for liquid level sensing. The image shows the custom sensor design that has been implemented on a flexible printed circuit board (PCB) to measure the liquid level inside the bottle. The <t>FDC1004</t> chip has been placed on the board for capacitive liquid sensing and labeled as U1. Two pull-up resistors for I 2 C signals have been mounted on flexible PCB, whereas C3 and C4 are decoupling capacitance. The P2 has 4 male pins for power supply and the I 2 C signals.
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captivatetm capacitive touch sensor technology  (Texas Instruments)
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Custom Sensor design for liquid level sensing. The image shows the custom sensor design that has been implemented on a flexible printed circuit board (PCB) to measure the liquid level inside the bottle. The <t>FDC1004</t> chip has been placed on the board for capacitive liquid sensing and labeled as U1. Two pull-up resistors for I 2 C signals have been mounted on flexible PCB, whereas C3 and C4 are decoupling capacitance. The P2 has 4 male pins for power supply and the I 2 C signals.
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Average 86 stars, based on 1 article reviews
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mpr121 12 key capacitive touch sensors  (Adafruit Industries)
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Adafruit Industries mpr121 12 key capacitive touch sensors
(a–d) Computer-aided design (CAD) renderings showing the modular enclosure, camera mount, and removable front panel. (e) Top-mounted USB3 machine-vision camera with visible and 850 nm infrared (IR) LED illumination for light and dark recordings. (f–g) Configurable arena fixtures for pellet wells and capacitive lickometers supporting fluid-access or operant tasks. (h) System wiring diagram linking the NVIDIA Jetson Orin Nano Super (6-core ARM CPU, 1024 CUDA cores, 32 tensor cores, 8 GB LPDDR5, 67 INT8 TOPS) to an RP2040 controller and <t>MPR121</t> capacitive sensors. (i) Example configuration showing a two-bottle choice and fixed-ratio 1 (FR1) feeding task. Each unit operates as an independent edge device performing on-board YOLO inference, sensor synchronization via TTL, and bidirectional task control—enabling scalable, low-cost, networked behavioral experiments without workstation-grade GPUs.
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Average 86 stars, based on 1 article reviews
mpr121 12 key capacitive touch sensors - by Bioz Stars, 2026-08
86/100 stars
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Custom Sensor design for liquid level sensing. The image shows the custom sensor design that has been implemented on a flexible printed circuit board (PCB) to measure the liquid level inside the bottle. The FDC1004 chip has been placed on the board for capacitive liquid sensing and labeled as U1. Two pull-up resistors for I 2 C signals have been mounted on flexible PCB, whereas C3 and C4 are decoupling capacitance. The P2 has 4 male pins for power supply and the I 2 C signals.

Journal: Biosensors

Article Title: A Microcontroller-Based Device for Liquid Intake and Lick Analysis in Rodents

doi: 10.3390/bios16050268

Figure Lengend Snippet: Custom Sensor design for liquid level sensing. The image shows the custom sensor design that has been implemented on a flexible printed circuit board (PCB) to measure the liquid level inside the bottle. The FDC1004 chip has been placed on the board for capacitive liquid sensing and labeled as U1. Two pull-up resistors for I 2 C signals have been mounted on flexible PCB, whereas C3 and C4 are decoupling capacitance. The P2 has 4 male pins for power supply and the I 2 C signals.

Article Snippet: The proposed system uses an FDC1004 capacitive sensor (Texas Instrument, USA) which has 4-channel capacitances to a digital converter for implementing capacitive sensing.

Techniques: Labeling

(a–d) Computer-aided design (CAD) renderings showing the modular enclosure, camera mount, and removable front panel. (e) Top-mounted USB3 machine-vision camera with visible and 850 nm infrared (IR) LED illumination for light and dark recordings. (f–g) Configurable arena fixtures for pellet wells and capacitive lickometers supporting fluid-access or operant tasks. (h) System wiring diagram linking the NVIDIA Jetson Orin Nano Super (6-core ARM CPU, 1024 CUDA cores, 32 tensor cores, 8 GB LPDDR5, 67 INT8 TOPS) to an RP2040 controller and MPR121 capacitive sensors. (i) Example configuration showing a two-bottle choice and fixed-ratio 1 (FR1) feeding task. Each unit operates as an independent edge device performing on-board YOLO inference, sensor synchronization via TTL, and bidirectional task control—enabling scalable, low-cost, networked behavioral experiments without workstation-grade GPUs.

Journal: bioRxiv

Article Title: SqueakPose Studio: An end-to-end platform for pose estimation and real-time edge-AI deployment

doi: 10.64898/2026.01.24.700912

Figure Lengend Snippet: (a–d) Computer-aided design (CAD) renderings showing the modular enclosure, camera mount, and removable front panel. (e) Top-mounted USB3 machine-vision camera with visible and 850 nm infrared (IR) LED illumination for light and dark recordings. (f–g) Configurable arena fixtures for pellet wells and capacitive lickometers supporting fluid-access or operant tasks. (h) System wiring diagram linking the NVIDIA Jetson Orin Nano Super (6-core ARM CPU, 1024 CUDA cores, 32 tensor cores, 8 GB LPDDR5, 67 INT8 TOPS) to an RP2040 controller and MPR121 capacitive sensors. (i) Example configuration showing a two-bottle choice and fixed-ratio 1 (FR1) feeding task. Each unit operates as an independent edge device performing on-board YOLO inference, sensor synchronization via TTL, and bidirectional task control—enabling scalable, low-cost, networked behavioral experiments without workstation-grade GPUs.

Article Snippet: Capacitive sensing for fluid intake was handled via Adafruit MPR121 12-key capacitive touch sensors, communicating with the RP2040 over I2C.

Techniques: Control