Wireless Weather Station

By Jerry Wasinger

I. Introduction

In the Midwest, the main topics of conversation may include the local football team or how the crops are doing. Inevitably though, the conversation always leads to the weather. Most of us take the weather for granted and don’t give it a second thought. But, in states like Kansas, Oklahoma, and Texas, weather is spelled with a capital “W” and is closely monitored by both individuals and the media. Weather is thunderstorms, tropical depressions, tornados, blizzards, squall lines, stationary fronts, cold fronts from Canadian, warm moist Gulf air, and hurricanes. The onset of any one of these events can be detected by monitoring a few basic conditions.

When you check the weather on the television or the radio, it’s always what conditions are like at the airport or some other remote location. But, what are conditions like in my backyard? To address this, I embarked on the design of the Wireless Weather Station. I had meant to do this project many years ago but two bits of technology finally spurred me into action: the first was the development of low-cost, solid state humidity sensors and the second was the availability of small, monolithic RF transceivers.

II. The Design

The Wireless Weather Station is composed of a remote station and a base station. The remote station is solar-powered and wakes up once a minute to collect and transfer data. The base station receives and buffers the incoming data and then transfers it via an RS232 connection to a PC for processing. Within each of the stations is a dedicated circuit card as well as a separate, RF circuit card. We’ll start our discussion with the remote station design.

A. Remote Station
The Remote Station consists of four functional sections: the sensors, the PIC16F873 microcontroller, the RF circuit, and the power supply. The schematic, shown in Figure2, shows the sensor and microprocessor areas.

For humidity sensing, I opted for the Humirel HS1101 capacitive sensor. This device, when combined with a CMOS 555 timer operating as an astable multivibrator, produces a signal with a humidity dependent frequency. To minimize temperature effects, it is important to use the Texas Instruments TLC555 device in this design. Refer to the HS1101 datasheet if another device is used. Also note that care must be taken at the node of the HS1101 and the 555. Stray capacitance values will lead to erroneous and unpredictable measurements. I chose to solder this node above the circuit card.

The relationship between the output frequency of the 555 and the relative humidity can be seen in Figure 1. A first order equation that relates relative humidity to frequency is:

R.H. = 565.1 – 0.0767 * f

A second order equation can be used for improved accuracy,:

R.H. = -6.4790E-06 * f2 + 1.0047E-02 * f + 2.7567E+02

• Relative Humidity vs. Timer Frequency

Temperature sensing is very straight-forward with the LM335. This output of this device is equal to the absolute temperature in degrees Kelvin divided by 100 or:

Vout=Temperature(K)/100

To determine the temperature in degrees C, use the equation:

ºC = 100 * Vout – 273

To determine the temperature in degrees Fahrenheit, use the equation:

ºF = 1.8 * ºC +32.2

= 1.8 * (100 * Vout – 273) + 32.2

= 180 * Vout - 459.2

At room temperature, this device outputs about 3volts.

Pressure sensing is provided by a Motorola MPX5100A, which operates from 0 to 16 PSI. However, we’re interested in only a very small part of that range. Barometric pressure readings fall between 28 and 32 inches of mercury. This translates to 13.75 to 15.72 PSI. To increase the dynamic range of the output, I added an amplifier circuit (U4), which subtracts about 3.7 volts from the sensor output and then multiplies the difference by 4. Since the MPX5100 can require as much as 10mA, Q1 was added to provide microprocessor-controlled switching.

I chose the Microchip PIC16F873 because it had the right mix of program and data memory, a 10-bit A/D, and three timers. Timer2 is used to measure the period of the humidity signal. The A/D is used to measure the temperature and pressure sensors as well as to monitor the battery voltage. To maximize accuracy I used an external 4.096 volt 0.1% reference from National Semiconductor. With the 10-bit A/D, this provides a resolution of 4mV per count.

III. Calibration

A. Temperature
The temperature sensor is typically accurate to within 2ºC before calibration. To improve accuracy, you will need an extension cable between the circuit board and the sensor as well as an ice-water slurry.

Place the sensor in the slurry and measure its output voltage using a voltmeter. Use the measured value in the following correction factor:

K=2.73/measured_value

Multiply your raw A/D readings by this correction factor to improve the precision of your temperature measurements.

B. Pressure
Your pressure sensor will require calibration and there are two possible methods to do it. The first method requires that you monitor your local weather channel for a couple of weeks while the second method necessitates some specialized equipment.

If you choose the first method, create a table and label the first column as Pressure Sensor and the second column as actual. Next, for about two weeks, monitor and record your local weather channel for the actual pressure. At the same time, measure and record the voltage across the pressure sensor. You will need to connect the Emitter and Collector of Q1 together so that power is routed to the sensor.

Enter your data into Excel and use a linear interpolation function to derive the equation:

Actual=K*measured+offset.

Use the following steps for the second method:

Using the above terms, barometric pressure can be calculated from the sensor voltage as:

Pressure = m * Voltage + b

C. Humidity
I found the humidity sensor to be pretty accurate and to not require calibration. However, be sure to follow the construction tips in this article to insure good performance.

IV. Weather Monitor Application Program

To take full advantage of the Remote Weather Monitor, I wrote a simple program in Visual Basic to collect the data from the base station, perform the calibration corrections and data conversions, and display it on the screen. Buttons are provided to display the basic data using a small window or to plot the data for the last 24 hours. See Figure 8 for a screen shot of the monitor window.

• Figure 8

V. Closing

An engineer’s work is never complete – there’s always room for improvement. A couple of things could be done to further embellish this design. First and foremost, the protocol between the remote and base stations could be modified to support multiple remotes. This would allow monitoring the climate, inside, outside, in the attic, etc.

The second improvement would be the addition of an anemometer. If time had permitted, I would have designed one based on ultrasonic transducers. This would have allowed measurements of wind speed and direction and, when combined with temperature, wind chill.

But, I’ll get to those projects later. According to my data, it’s too nice of a day to be inside.

VI. Appendix

A. Ensuring Data Integrity with Hamming Codes
In mission critical applications when there is only one opportunity to exchange data, it is common to employ Forward Error Correction, or FEC. One application of this technique is for the data sent from a distant satellite – because of the time delays inherent with the great distances between a space probe and ground station, it is more efficient to encode the transmitted data with Forward Error Correction than to request a retransmission. FEC is accomplished by transmitting extra bits with an n-bit sequence so that errors can be detected and corrected by the receiver. One common implementation of FEC is through the use of Hamming codes.

In our application, the basic data block consists of a 10-bit A/D value. By adding four parity bits for the Hamming code, we increase our block size to 14 bits but with the added benefit of being able to detect and correct a single bit error. Consider the following data arrangement:
 

P1, P2, P3, and P4 are our parity bits while D9-D0 are our A/D reading. To calculate each of the parity bits, we use modulo-1 arithmetic. With modul0-1 arithmetic, the sum of an even number of 1’s results in a zero while the sum of an odd number of 1’s results in a 1.

Each of the parity bits is calculated using the equations below:

P1=D9+D8+D6+D5+D3+D1

P2=D9+D7+D6+D4+D3+D0

P4=D8+D7+D6+D2+D1+D0

P8=D5+D4+D3+D2+D1+D0
 

On the receive side, the Check bits are calculated from:

C1=P1+D9+D8+D6+D5+D3+D1

C2=P2+D9+D7+D6+D4+D3+D0

C4=P4+D8+D7+D6+D2+D1+D0

C8=P8+D5+D4+D3+D2+D1+D0
 

If there are no errors in the data, the value of the nibble formed by C8-C4-C2-C1 will be zero. If there is an error, the value of C8-C4-C2-C1 will contain the bit location that requires correction. To correct the bit, just invert its value!
 

Examples:

Let’s assume that we have an A/D value of 3A8h or 1111001000b. Our transmitted Hamming code for this block becomes:

On the receive side we might receive the following:

When the data is received correctly, the code values are:

C8=1+0+0+1+0+0+0=0

C4=1+1+1+1+0+0+0=0

C2=0+1+1+1+0+1+0=0

C1=0+1+1+1+0+1+0=0
 

Thus the check code, C8C4C2C1, is equal to 0000b when the data is correctly received.

When an error occurs in the ninth bit, the check code values are:

C8=1+1+0+1+0+0+0=1

C4=1+1+1+1+0+0+0=0

C2=0+1+1+1+0+1+0=0

C1=0+1+1+1+1+1+0=1
 

C8C4C2C1=1001 indicates the erroneous bit position of 9.

Finally if an error occurs in the third bit, we get:

C8=1+0+0+1+0+0+0=0

C4=1+1+1+1+0+0+0=0

C2=0+0+1+1+0+1+0=1

C1=0+0+1+1+0+1+0=1

C8C4C2C1=0011 confirms the erroneous bit position of 3.

B. Images - click for a larger view

• Remote Station Assembly. Note Transmitter board on left
• Remote Station, Antenna, and Solar Cell
• Base Station Assembly

C. Source and design Files