Connect 2015 Smoking Salmon with Splunk and Raspberry Pi
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This document discusses using a Raspberry Pi and sensors to monitor temperature and humidity while cold smoking salmon. It provides assumptions about cold smoking, describes the equipment used including electronics and code to connect DHT sensors and record data. It also provides instructions for dry curing and smoking the salmon. The motivation is discussed as an affordable way to smoke salmon for significant cost savings compared to store-bought smoked salmon. Future plans mentioned expanding the system.
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Connect 2015 Smoking Salmon with Splunk and Raspberry Pi
- 1. Smoking Salmon with Splunk and Raspberry Pi Greg Dostatni
- 2. Assumptions Cold Smoking Requires temperatures between 20°C and 30°C Raspberry Pi Tiny computer used by hobbyists for just about anything Splunk Software used for searching, visualizing and analyzing machine generated data
- 3. Equipment
- 4. Electronics
- 6. Code* #!/usr/bin/python import dhtreader, time, os, sys, os.path type=22 pins =(18,) dhtreader.init() time.sleep(3) for loop in range(SAMPLECOUNT): for pin in pins: time.sleep(0.5) val = dhtreader.read(type,pin) if val: temp, hum = val sensors[pin]["count"] += 1 sensors[pin]["temperature"] += temp sensors[pin]["humidity"] += hum time.sleep(0.5) for pin in pins: if sensors[pin]["count"] > 0: sensors[pin]["tempoutput"]=str(sensors[pin]["temperature"] / sensors[pin]["count"]) sensors[pin]["humoutput"]=str(sensors[pin]["humidity"] / sensors[pin]["count"]) else: sensors[pin]["tempoutput"]="ERR" sensors[pin]["humoutput"]="ERR" sensors[pin]["errors"]=str(SAMPLECOUNT- sensors[pin]["count"]) # output averages fpw.write( "%s,"%time.ctime() + ','.join(["%s,%s"%(sensors[x]["tempoutput"],sensors[x]["humoutput" ]) for x in pins])+"n") sys.stderr.write("%s, samples=%d, "%(time.ctime(),SAMPLECOUNT)+','.join(["S%d_errorcount=%s"% (x,sensors[x]["errors"]) for x in pins])+"n”) *Complete source available in comments on this slide.
- 7. Dry Cure 4 cups brown sugar 1 cup salt Spices (optional) Video instructions at http://youtu.be/Jk3xl6H9o94
- 10. Motivation Salmon economics Salmon Filet $9 / lbs. Typical batch 4 lbs. Finished weight 2.8 lbs. C. Smoked Salmon $ 40 - 45 / lbs. Savings $ 70 - 85 CFO’s approval … Priceless
- 11. Future Plans
- 12. Future Plans #2
Editor's Notes
- Inexpensive diy smoker
- Diy breakout board for rapidly connecting sensors.
- #!/usr/bin/python import dhtreader import time import os, sys, os.path type=22 #pins=(23,24,25) pins =(18,) LOGDIR="/var/log/sensor" LOGFNAME = "sensors.csv" SAMPLECOUNT = 5 HEADER="Timestamp," + ','.join(["S%d_Temp,S%d_Humidity"%(x,x) for x in pins])+"\n" dhtreader.init() time.sleep(3) if not os.path.exists(os.path.join(LOGDIR, LOGFNAME)) : fpw=open(os.path.join( LOGDIR ,LOGFNAME),"a+") fpw.write(HEADER) else: fpw=open(os.path.join( LOGDIR ,LOGFNAME),"a+") # Sampling loop. # Sample 5 times each sensor , 1 second between sample runs # Record averages in CSV, Output error rate to stderr sensors={} for pin in pins: sensors[pin]={"count":0,"temperature":0,"humidity":0} for loop in range(SAMPLECOUNT): for pin in pins: time.sleep(0.5) val = dhtreader.read(type,pin) if val: temp, hum = val sensors[pin]["count"] += 1 sensors[pin]["temperature"] += temp sensors[pin]["humidity"] += hum time.sleep(0.5) for pin in pins: if sensors[pin]["count"] > 0: sensors[pin]["tempoutput"]=str(sensors[pin]["temperature"] / sensors[pin]["count"]) sensors[pin]["humoutput"]=str(sensors[pin]["humidity"] / sensors[pin]["count"]) else: sensors[pin]["tempoutput"]="ERR" sensors[pin]["humoutput"]="ERR" sensors[pin]["errors"]=str(SAMPLECOUNT-sensors[pin]["count"]) # output averages fpw.write( "%s,"%time.ctime() + ','.join(["%s,%s"%(sensors[x]["tempoutput"],sensors[x]["humoutput"]) for x in pins])+"\n") sys.stderr.write("%s, samples=%d, "%(time.ctime(),SAMPLECOUNT)+','.join(["S%d_errorcount=%s"%(x,sensors[x]["errors"]) for x in pins])+"\n" )
- Spike corresponds to when I accidently dumped a lot of snow on one of the sensors.
- Without data you don’t know what you get. Above: Temperature and humidity of my dryer (two loads). There is a fair amount of time spent just warming up the clothes without removing any more water. Below: A small bar fridge we use to store breast milk for the little one. The temperature fluctuates over a 5 degree range, which is much higher than expected. I realize that the bottle of milk will have a much better stability, but the range did surprise me.
- This is a 3d model of my house. One of the perksof being married to a structural engineer. I want to make it into a house dashboard inside of our home Splunk.