The previous thread was locked so I am opening up a new thread because I am so pleased with thermistors used with a Pico W. I have had a working system on an Alaskan island town for several years with great results.
Today I am setting up a new system here in NC.
I am using waterproof Thermistors, 10k, NTC.![Image]()
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Here is the part of the total code that deals with my Steinhart-Hart equation algorithm:
I decided to run a test of accuracy and tracking because the difference between the HWS and HWR is of critcal importance and the accuracy is secondary as long as the two sensors track properly. My test today displayed 99.68% accuracy for tracking (deltaT between sensors) and 99.5% accuracy for actual temperature. Outstanding for cheap ($5 each) waterproof Thermistors and the PICO W.
![Image]()
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here is raw data:Now, for a confession. I had an older set of beta etc for the algorithm and I was having trouble getting the results I was needing. I turned to Grok AI and fed it the code and the results I was getting. In four iterations where Grok made suggestions and I tried them and sent back raw data, Grok tweaked my code to the finished almost perfect results.
Here is the graph of just the first 10 minutes,
![Image]()
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Today I am setting up a new system here in NC.
I am using waterproof Thermistors, 10k, NTC.
(right mouse to open in new tab, or else it takes you out of forum)
Here is the part of the total code that deals with my Steinhart-Hart equation algorithm:
Code:
thermistor28 = machine.ADC(28) #hwr, hot water return, 10K NTC thermistor typicalthermistor27 = machine.ADC(27) #hws, hot water supply temperatureboiler = Pin(14, Pin.IN, Pin.PULL_UP) #boiler status while True: ##### HWR (thermistor28) temperature28_value = thermistor28.read_u16() Vr28 = 3.3 * float(temperature28_value) / 65535 Rt28 = 9940 * Vr28 / (3.3 - Vr28) ln_rt28 = math.log(Rt28) temp28 = 1 / (0.0015350 + 0.00013850 * ln_rt28 + 0.0000008100 * (ln_rt28 ** 3)) Cel28 = temp28 - 273.15 Fah28 = Cel28 * 1.8 + 32 utime.sleep_ms(200) ##### HWS (thermistor27) temperature27_value = thermistor27.read_u16() Vr27 = 3.3 * float(temperature27_value) / 65535 Rt27 = 9910 * Vr27 / (3.3 - Vr27) ln_rt27 = math.log(Rt27) temp27 = 1 / (0.0015350 + 0.00013850 * ln_rt27 + 0.0000008100 * (ln_rt27 ** 3)) Cel27 = temp27 - 273.15 Fah27 = Cel27 * 1.8 + 32 utime.sleep_ms(200)I decided to run a test of accuracy and tracking because the difference between the HWS and HWR is of critcal importance and the accuracy is secondary as long as the two sensors track properly. My test today displayed 99.68% accuracy for tracking (deltaT between sensors) and 99.5% accuracy for actual temperature. Outstanding for cheap ($5 each) waterproof Thermistors and the PICO W.
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here is raw data:
Code:
Calibration Test of Two Thermistors, 1Ok, NTC10-23-2025 HWS HWR DELTA Ttime06:55:3171.8071.740.0606:56:0972.1671.580.5806:56:48185.50181.763.7406:57:27184.71184.220.4906:58:06181.64179.532.1106:58:45177.69176.661.0306:59:24174.89173.761.1307:00:02172.33172.020.3107:00:41171.41170.061.3407:01:20168.84167.781.0607:01:59166.85165.451.4007:02:38164.43163.540.8907:03:16162.20161.560.6407:03:55160.03159.410.6207:04:34157.71157.86-0.1507:05:13156.31155.920.3907:05:52154.93154.330.6007:06:31152.95152.670.2807:07:10151.33151.150.1807:07:48149.44149.260.1707:08:27147.88148.00-0.1207:09:06146.64146.370.2707:09:45146.07145.520.5507:10:24144.48144.030.4507:11:02143.01142.740.2607:11:41142.28141.300.9807:12:20140.41140.240.1707:12:59139.71139.360.3507:13:38138.32138.150.1707:14:19137.04136.690.3407:14:57136.28135.770.5107:15:36135.36135.100.2607:16:15133.62133.78-0.1607:16:54132.97132.720.2507:17:33131.76131.99-0.2307:18:12131.20130.710.4907:18:51130.57129.690.8807:19:30129.63129.300.3307:20:09128.07128.13-0.0607:20:47127.15127.21-0.0607:21:26126.62126.600.0207:22:05125.87126.15-0.2807:22:44124.82125.17-0.3507:23:23124.37124.43-0.0507:24:02124.00123.460.5407:24:41122.82122.650.1707:25:19121.95121.860.1007:25:58121.38121.71-0.3407:26:37121.23120.630.6007:27:16120.09120.060.0307:27:55119.31119.42-0.1107:28:34118.96118.860.1007:29:13118.61118.160.4507:29:51117.49117.250.2407:30:30117.28116.630.6507:31:09116.87116.150.7207:31:48115.64115.540.1007:32:27115.43115.130.3007:33:05114.62114.72-0.1007:33:44114.08113.710.3707:34:27113.81112.840.9707:35:06113.34112.780.5707:35:45112.35112.250.1007:36:23112.02111.590.4307:37:02111.36111.130.2307:37:41111.23110.470.7607:38:20110.12110.28-0.1607:38:59109.99109.630.3607:39:38109.73108.980.7507:40:16108.83108.470.3607:40:55108.25108.150.1007:41:34107.74107.700.0407:42:13107.23107.38-0.1507:42:52106.85106.810.0407:43:30106.41106.69-0.2707:44:09106.29106.250.0407:44:48105.47105.74-0.2707:45:27105.34105.240.1007:46:06105.22105.050.1707:46:45105.16104.620.5407:47:24104.35104.060.2907:48:02104.23103.870.3507:48:41103.30103.44-0.1407:49:20103.42103.130.2907:49:59103.12102.640.4707:50:40102.93102.220.7207:51:19102.02101.670.3507:51:57101.47101.430.0407:52:36101.23101.060.1707:53:15100.99100.700.2907:53:54100.32100.64-0.3207:54:33100.08100.040.0507:55:11100.3299.800.5307:55:50100.0299.500.5207:56:2999.3699.020.3407:57:0899.0798.660.4007:57:4798.7198.600.1107:58:2698.5998.490.1107:59:0498.0697.890.1707:59:4397.8897.480.4008:00:2297.2997.30-0.0108:01:0196.8296.540.2808:01:4096.5396.480.0508:02:1896.4196.42-0.0108:02:5796.1296.19-0.0708:03:3695.6595.490.1608:04:1595.8995.720.1608:04:5495.7195.310.4008:05:3295.4294.730.6908:06:1194.9694.560.4008:06:5094.3294.33-0.0108:07:2994.3293.920.4008:08:0893.9794.21-0.2408:08:4794.2093.410.8008:09:2593.3493.35-0.0108:10:0493.4093.060.3408:10:4393.2392.890.3408:11:2293.0692.610.4508:12:0392.0892.49-0.4108:12:4292.5492.210.3408:13:2192.0891.980.1108:14:0191.7491.92-0.1808:14:4091.8691.410.4508:15:1991.2991.130.1608:15:5891.0691.13-0.0608:16:3790.7890.730.0508:17:1690.8490.620.2208:17:5590.7890.620.1608:18:3390.7890.560.2208:19:1290.5590.390.1608:19:5190.3890.110.2808:20:3090.2190.110.1108:21:0990.1689.770.3908:21:4789.4889.210.2808:22:2689.4889.320.1608:23:0589.2689.43-0.1708:23:4488.9288.870.0508:24:2388.8188.200.6108:25:0288.8188.430.3908:25:4088.8788.200.6708:26:1988.2087.980.2208:26:5888.4887.870.6108:27:3988.2588.040.2208:28:1787.5987.200.3808:28:5687.4887.54-0.0608:29:3587.3787.370.0008:30:1487.4886.930.5508:30:5386.9886.930.0508:31:3186.9286.650.2708:32:1086.5986.430.1608:32:4986.1586.21-0.0608:33:2886.4386.320.1108:34:0786.1585.880.2708:34:4686.1585.550.6008:35:2486.1085.820.2708:36:0385.9985.550.4408:36:4285.9985.660.3308:37:2185.2785.38-0.1108:38:0085.2785.33-0.0608:38:3985.4984.780.7108:39:1785.1184.890.2208:39:5685.0084.670.3308:40:3584.8984.620.2708:41:1484.6784.450.2208:41:5384.7883.691.0908:42:3284.2984.130.1608:43:1084.2383.960.2708:43:4983.8583.310.5408:44:2884.0283.690.3308:45:0784.0783.580.4908:45:4683.4783.040.4308:46:2483.3682.930.4308:47:0383.5883.040.5408:47:4283.7482.661.0908:48:2183.1582.440.7008:49:0082.9382.820.1108:49:3982.5082.390.1108:50:1782.7182.280.4308:50:5682.7782.390.3808:51:3582.2881.960.3208:52:1482.5581.960.5908:52:5381.4781.63-0.1608:53:3281.8581.740.1108:54:1082.1281.740.3808:54:4982.0181.420.5908:55:2881.2581.250.0008:56:0781.5881.200.3808:56:4681.2081.150.0508:57:2581.6381.250.3808:58:0381.4281.150.2708:58:4281.3680.770.5908:59:2181.1579.861.2909:00:0080.7280.660.0509:00:3980.8280.390.4309:01:1880.4080.290.1109:01:5680.6179.810.8009:02:3580.3480.230.1109:03:1480.8879.970.9109:03:5380.5080.070.4309:04:3279.9179.700.2209:05:1079.8679.590.2709:05:4980.1879.750.4309:06:2879.7079.81-0.1109:07:0779.7579.320.4309:07:4679.8679.430.4309:08:2479.6579.160.4809:09:0779.2279.38-0.1609:09:4679.7079.160.5409:10:2579.2279.160.0509:11:0379.2278.840.3709:11:4279.3878.840.5309:12:2179.0178.900.1109:13:0079.0178.840.1609:13:3979.1778.530.6409:14:1778.9078.530.3709:14:5678.6378.310.3209:15:3578.2678.210.0509:16:1478.6978.100.5909:16:5378.4778.210.2709:17:3178.6377.680.9609:18:1078.3178.150.1609:18:4978.4277.680.7509:19:2878.1078.47-0.3709:20:0778.0577.990.0609:20:4678.2677.890.3709:21:2577.8977.99-0.1009:22:0477.7877.680.1109:22:4277.8477.570.2709:23:2177.9477.460.4809:24:0477.7377.040.6909:24:4377.5777.410.1609:25:2277.2077.36-0.1609:26:0077.3177.040.2709:26:3977.8977.250.6409:27:1877.4176.780.6409:27:5777.3676.930.43Here is the graph of just the first 10 minutes,
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Statistics: Posted by shore — Fri Oct 24, 2025 1:03 am — Replies 0 — Views 54