update

loop/SARA_send_data_v2.py

@@ -40,7 +40,7 @@ CSV PAYLOAD (AirCarto Servers)
     8   -> min_noise
     9   -> envea_no2
     10  -> envea_h2s
-    11  -> envea_o3
+    11  -> envea_nh3
     12  -> 4G signal quality,
     13  -> PM 0.2μm to 0.5μm quantity (Nb/L)
     14  -> PM 0.5μm to 1.0μm quantity (Nb/L)
@@ -202,10 +202,13 @@ config_file = '/var/www/nebuleair_pro_4g/config.json'
 config = load_config(config_file)
 baudrate = config.get('SaraR4_baudrate', 115200)       #baudrate du sara R4
 device_id = config.get('deviceID', '').upper()         #device ID en maj
-need_to_log = config.get('loop_log', False)            #inscription des logs
+bme_280_config = config.get('BME280/get_data_v2.py', False)          #présence du BME280
+envea_cairsens= config.get('envea/read_value_v2.py', False)
 send_aircarto = config.get('send_aircarto', True)      #envoi sur AirCarto (data.nebuleair.fr)
 send_uSpot = config.get('send_uSpot', False)           #envoi sur MicroSpot ()
 selected_networkID = config.get('SARA_R4_neworkID', '') 
+npm_5channel = config.get('NPM/get_data_modbus.py', False)   #5 canaux du NPM
+
 modem_config_mode = config.get('modem_config_mode', False)            #modem 4G en mode configuration
 
 #update device id in the payload json
@@ -279,8 +282,9 @@ try:
                          
     '''
     print('<h3>START LOOP</h3>')
-    print("Getting NPM values")
-    # Retrieve the last sensor readings
+
+    #NEXTPM
+    print("➡️Getting NPM values")
     cursor.execute("SELECT * FROM data_NPM ORDER BY timestamp DESC LIMIT 1")
     last_row = cursor.fetchone()
     # Display the result
@@ -313,6 +317,74 @@ try:
     else:
         print("No data available in the database.")
 
+    #NextPM 5 channels
+    if npm_5channel:
+        print("➡️Getting NextPM 5 channels values")
+        cursor.execute("SELECT * FROM data_NPM_5channels ORDER BY timestamp DESC LIMIT 6")
+        rows = cursor.fetchall()
+        # Exclude the timestamp column (assuming first column is timestamp)
+        data_values = [row[1:] for row in rows]  # Exclude timestamp
+        # Compute column-wise average
+        num_columns = len(data_values[0])
+        averages = [round(sum(col) / len(col)) for col in zip(*data_values)]
+
+        # Store averages in specific indices
+        payload_csv[13] = averages[0]  # Channel 1
+        payload_csv[14] = averages[1]  # Channel 2
+        payload_csv[15] = averages[2]  # Channel 3
+        payload_csv[16] = averages[3]  # Channel 4
+        payload_csv[17] = averages[4]  # Channel 5
+
+    #BME280
+    if bme_280_config:
+        print("➡️Getting BME280 values")
+        cursor.execute("SELECT * FROM data_BME280 ORDER BY timestamp DESC LIMIT 1")
+        last_row = cursor.fetchone()
+        if last_row:
+            print("SQLite DB last available row:", last_row)
+            BME280_temperature = last_row[1]  
+            BME280_humidity = last_row[2]
+            BME280_pressure = last_row[3]
+
+            #Add data to payload CSV
+            payload_csv[3] = BME280_temperature 
+            payload_csv[4] = BME280_humidity
+            payload_csv[5] = BME280_pressure
+
+            #Add data to payload JSON
+            payload_json["sensordatavalues"].append({"value_type": "BME280_temperature", "value": str(BME280_temperature)})
+            payload_json["sensordatavalues"].append({"value_type": "BME280_humidity", "value": str(BME280_humidity)})
+            payload_json["sensordatavalues"].append({"value_type": "BME280_pressure", "value": str(BME280_pressure)})
+        else:
+            print("No data available in the database.")
+
+    #envea
+    if envea_cairsens:
+        print("➡️Getting envea cairsens values")
+        cursor.execute("SELECT * FROM data_envea ORDER BY timestamp DESC LIMIT 6")
+        rows = cursor.fetchall()
+        # Exclude the timestamp column (assuming first column is timestamp)
+        data_values = [row[1:] for row in rows]  # Exclude timestamp
+        # Compute column-wise average, ignoring 0 values
+        averages = []
+        for col in zip(*data_values):  # Iterate column-wise
+            filtered_values = [val for val in col if val != 0]  # Remove zeros
+            if filtered_values:
+                avg = round(sum(filtered_values) / len(filtered_values))  # Compute average
+            else:
+                avg = 0  # If all values were zero, store 0
+            averages.append(avg)
+
+        # Store averages in specific indices
+        payload_csv[9] = averages[0]  # envea_no2
+        payload_csv[10] = averages[1]  # envea_h2s
+        payload_csv[11] = averages[2]  # envea_nh3
+
+         #Add data to payload JSON
+        payload_json["sensordatavalues"].append({"value_type": "CAIRSENS_NO2", "value": str(averages[0])})
+        payload_json["sensordatavalues"].append({"value_type": "CAIRSENS_NO2", "value": str(averages[1])})
+        payload_json["sensordatavalues"].append({"value_type": "CAIRSENS_NH3", "value": str(averages[2])})
+
 
     print("Verify SARA R4 connection")