Linx

How to Use the LC Series LINX Modules

by Lee Rumsey

These are basic instructions on hooking up the modules. This document is split into five nifty sections:

For data sheets on the LINX modules, see this web site: http://www.linxtechnologies.com. Click on the RF Modules link. Then click on the Manuals item under the LC Series heading. READ through the LC Series data sheets to get an understanding of their function. This will reduce the likelihood of errors.

Necessary Parts

TX board (1) Smaller PC board; has TXM-XXX-LC chip on it
RX board (1) Larger PC board; has RXM-XXX-LC chip on it
Antenna (2) Either whips or helical antennas
RG-174 50W coax cable Available from ECE Store; for connecting antennas
22 ga hookup wire Should be laying around the 445 lab
390 W, 1/4 W resistor (1) Needed for 5V operation

Before we start

  1. Learn to solder. You will be making some delicate connections, so practice if you don't know how. Also be sure to use solder sparingly- big blobs will likely result in damage or malfunctions.
  2. You should have the parts listed above. Get them from a TA.
  3. Make sure the transmitter and receiver are running on the same frequency. Do this by checking the model number on the surface mount package. For example, a 418 MHz TX module will be labeled TXM-418-LC, and a 315 MHz RX module will be RXM-315-LC.

Transmitter Assembly

The LINX transmitter is the smaller of the two modules. It runs on between +2.7 and 5.2 VDC. We will use a +5 VDC power supply, so that the data input can be a TTL level signal. DO NOT apply a voltage greater than Vcc on the data input pin!

Step 1. Acclimate yourself with the circuit we are building:
schematic

Step 2. Place the TX board with chip side facing UP. The writing on the chip should be right side up, with a little wire coming off the top. This wire is GROUND. A '1' or a small dot should be visible on the lower left-hand corner of the chip. GROUND is also connected to the center bus strip on the board.

Step 3. Solder the 390 W resistor from pin 4 (lower right-hand corner) to ground. This sets the chip to accept 5 VDC. NOTE: make all connections on the top of the board. DON'T feed any leads through the holes. There are connections on the other side!

Step 4. Carefully solder a 3-inch wire to pin 2. This will be the DATA input. DO NOT apply a voltage greater than Vcc on the data input pin!

Step 5. Carefully solder a 3-inch wire to pin 7. This will be the VCC power input. REMEMBER: +5 VDC ONLY on this pin!

Step 6a. If you have a HELICAL COIL antenna, solder a short (2 inch) length of coax cable to pin 5 and GROUND. The inner conductor is the RF signal, and the outer shield goes to GROUND. Now solder the helical coil to the other end of the coax to form a magnetic loop. (You may need to extend the shield connection with a separate wire.)

Step 6b. If you have a WHIP antenna, solder the coax cable directly to pin 5 and GROUND. The inner conductor is the RF signal, and the outer shield goes to GROUND.

Here is the completed TX board assembly:
board


Receiver Assembly

The LINX receiver is the larger of the two modules. It runs on between +4 and 5.2 VDC. We will use a +5 VDC power supply. GROUND is the center vertical strip on the solder side.

Step 1. Acclimate yourself with the circuit we are building:
circuit

Step 2. Place the RX board with chip side facing DOWN, with the solder side UP. Orient the board so that one wire comes off the top, while another comes off the left of the board. The top wire is the power connection; the left wire is ground. Pin 1 of the chip is actually at the lower left with this orientation; it is identified on the chip by a '1' or a dot.

Step 3. Carefully solder a 3-inch wire to pin 5 (top left solder pad connected to the chip). This will be the DATA output.

Step 4a. If you have a HELICAL COIL antenna, solder a short (2 inch) length of coax cable to pin 1 and GROUND. The inner conductor is the RF signal, and the outer shield goes to GROUND. Now solder the helical coil to the other end of the coax to form a magnetic loop. (You may need to extend the shield connection with a separate wire.)

Step 4b. If you have a WHIP antenna, solder the coax cable directly to pin 1 and GROUND. The inner conductor is the RF signal, and the outer shield goes to GROUND.

Step 5. IMPORTANT! If there is a connection to pin 10 on the Linx chip, carefully desolder it, leaving the others intact. It is misconnected.

Here is the completed RX board assembly:
complete


Testing and Operation

Now we'll see if these modules work. If you are working with 418 MHz chips, then a reference receiver - transmitter pair are available for testing. Otherwise, you better hope you made the right connections? we don't have anything to test the 315 MHz RX/TX chips, except maybe another functioning pair of modules.

Step 1. TESTING THE TRANSMITTER. Refer to the schematic for the TX module we just assembled. Connect +5 VDC to the power lead, and ground the GROUND lead.

Step 2. Turn on or plug in the power. Use +5 VDC only! If anything is heating up, UNPLUG the module and check your connections!

Step 3. Set up a function generator the make a 1 kHz TTL compatible square wave (i.e. it swings between 0 and +5V only!) Connect this signal to the data input lead from the module. If anything is heating up, UNPLUG the module and check your connections!

Step 4. Plug the data output of the reference receiver into an oscilloscope. ASK A TA FOR ASSISTANCE! If all is well, a 1 kHz square wave should appear on the screen. You are done; wire your module into the rest of your circuit.

NOTE: For a flaky power supply, a bypass capacitor (10 uF electrolytic) may be necessary between power and ground on YOUR board.

Step 5. TESTING THE RECEIVER. Refer to the schematic for the RX module we just assembled. Connect +5 VDC to the power lead, and ground the GROUND lead

Step 6. Turn on or plug in the power. Use +5 VDC only! If anything is heating up, UNPLUG the module and check your connections!

Step 7. Set up a function generator the make a 1 kHz TTL compatible square wave (i.e. it swings between 0 and +5V only!) Connect this signal to the data input on the reference transmitter. ASK A TA FOR ASSISTANCE! If anything is heating up, UNPLUG the module and check your connections!

Step 8. Connect the data output of your receiver module into an oscilloscope. If all is well, a 1 kHz square wave should appear on the screen. You are done; wire your module into the rest of your circuit.

THE END.

Navigation Vest Suite For People With Eye Disability

Jiwoong Jung, Haoming Mei, Pump Vanichjakvong

 Navigation Vest Suite For People With Eye Disability

Featured Project

# Navigation Vest Suite For People With Eye Disability

Team Members & Experiences:

- Jiwoong Jung (jiwoong3): Experienced in Machine Learning, and some Embedded programming. Worked on many research and internships that requires expertise in Machine Learning, Software Engineering, Web Dev., and App Dev. Had some experience with Embedded programming for Telemetry.

- Haoming Mei (hmei7): Experienced in Embedded programming and PCB design. Worked with projects like lights, accelerometer, power converter, High-Fet Board, and motor control for a RSO that involve understanding of electronics, PCB design, and programming with STM32 MCUs.

- Pump Vanichjakvong (nv22): Experienced with Cloud, Machine Learning, and Embedded programming. Done various internships and classes that focuses on AI, ML, and Cloud. Experience with Telemetry and GPS system from RSO that requires expertises in SPI, UART, GPIOs, and etc with STM32 MCUs.

# Problem

People with Eye Disability often face significant challenges navigating around in their daily lives. Currently, most available solutions ranges like white canes and guide dogs to AI-powered smart glasses, many of which are difficult to use and can cost as much as $3,000. Additionally, problems arises for people with disability, especially in crowded/urban areas, and that includes injuries from collision with obstacles, person, or from terrains. According to the U.S department of Transportation's 2021 Crash Report , 75% of pedestrian fatalities occurred at locations that were not intersections. Thus we aim to design a navigation vest suite to help people with eye disability to deal with these issues.

https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/813458.pdf

# Solution

We have devised a solution which helps ease visually impaired individuals in daily activities such as walking from two places, or navigating around a building with multiple obstacles. Our focus will for out-door navigation in urban areas, where obstacles, terrain, and pedestrians. But, if time permits we will also deal with traffics and crosswalks.

In order to achieve this, we will be utilizing 3 main components:

- Lidar sensors to help the wearer with depth perception tasks

- Vibration Motors to aid navigation (turning left/right)

- Magnetometer to enable more accurate GPS coordination

All the above components will contribute to the sensory fusion algorithm.

# Solution Components

## Subsystem 1

### Microcontroller System

We are planning to use a STM32 microcontroller as main processing unit for sensory data from lidar sensors (magnetometer and GPS if time permits) and object detection data from the **machine learning system**, and direction data from navigation app (our design on phone). We will use these information to generate vibration in the direction the wearer should navigate.

### Power Systems

The whole system will be battery-powered by a battery module, which contains 5V battery-cells. It will be connected to the **Microcontroller System**, which will also supply it to the **Machine Learning System**. We will also implement the necessary power protection, buck converter, regulator, and boost converters as necessary per sensors or components.

- Battery Module Pack

- Buck Converter (Step-Down)

- Boost Converter (Step-Up)

- Voltage Regulator

- Reverse Polarity Protection

- BMS

## Subsystem 2

### Navigation Locator Systems

Our navigation system will consist of an App which directly connects to the Google Maps API, paired with our existing sensors. We plan to utilize a magnetometer sensor, which will indicate the direction the user is facing (North, South, East, West, .etc). In order to pinpoint which direction the wearer needs to be heading, our built-in LiDAR sensors will enable us to create a SLAM (Simultaneous Localization and Mapping) to build a map of the environment. With these systems in place, we would be able to assist users in navigation. To deal with Terrain hazards, we will use the LiDAR to sensors to assist us in dealing with elevation changes the user needed to make.

- LiDAR

- Android App (Connected to Google API)

- Magnetometer

- Vibration Motors

Extra Features (if time permits):

- Audio Output (Text to Speech Generation from Raspberry PI 5 sends to microcontroller through AUX cable )

## Subsystem 3

### Machine Learning Systems

- We plan to employ a object detection model on a 16GB Raspberry PI 5 (already) along with a PI camera to detect objects, signs, and people on the road, which will be feed to the microcontroller

- Raspberry PI 5

- PI Camera

a) The image video model will be expected to be less than 5 billion parameters with convolutional layers, running on device in raspberry pi Obviously the processing power on the raspberry pi is expected to be limited, however we are planning to accept the challenge and find out ways to improve the model with limited hardware capabilities.

b) If the overall project for subtask a) becomes arduous or time consuming, we can utilize api calls or free open source models to process the image/video in real time if the user wants the feature enabled. The device is paired with the phone via the wifi chip on the raspberry pi to enable the API call. Some of the best candidates we can think of are the YOLO family models, MMDetection and MMTracking toolkit, or Detectron2 model that is developed by Facebook AI Research that supports real time camera feedbacks.

# Criterion For Success

### Navigational Motor/Haptic Feedback

1) The Haptic feedback (left/right vibration) should perfectly match with the navigation directions received from the app (turn left/right)

2) Being able to Detect Obstacles, Stairs, Curbs, and people.

3) Being able to detect intersections infront and the point of turn through the lidar sensory data.

4) Being able to obey the haptic feedback patterns that is designed. (tap front for walking forward, tap right to go right etc...)

### Object Detection

1) Using the Illinois Rules of the Road and the Federal Manual on Uniform Traffic Control Device Guidelines, we will be using total of 10-30 distinct pedestrian road signs to test the object detection capability. We will be using a formal ML testing methods like geometric transformations, photometric transformations, and background clutter. Accuracy will be measured by the general equation (Total Number of correctly classified Datasets)/(Total Number of Datasets)

2) The ML Model should be able to detect potential environmental hazards including but not limited to Obstacles, Stairs, Curbs, and people. We are planning onto gather multiple hazard senarios via online research, surveys, and in-person interviews. Based on the collected research, we will be building solid test cases to ensure that our device can reliably identify potential hazards. More importantly, we are planning design strict timing and accuracy measures metrics.

3) The ML model should be able to detect additional road structures such as curbs, crosswalks, and stairs to provide comprehensive environment awareness. We will be utilizing different crosswalks located on north quad and utilize the accuracy measurement techniques mentioned in 1)

### Power and Battery Life

1) The device should support at least 3 hours of battery life.

2) The device should obey the IEC 62368-1 safety standard. IEC 62368-1 safety standard lays out different classes such as ES1, ES2, and ES3 that considers electrical and flame

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