diff --git a/homepage/style.css b/homepage/style.css
index 6469e1c..ba5e360 100644
--- a/homepage/style.css
+++ b/homepage/style.css
@@ -349,6 +349,36 @@ button:hover {
   width: 20%;
 }
 
+.slider {
+  -webkit-appearance: none;
+  width: 33%;
+  height: 15px;
+  border-radius: 5px;
+  background: #d3d3d3;
+  outline: none;
+  opacity: 0.7;
+  -webkit-transition: .2s;
+  transition: opacity .2s;
+}
+
+.slider::-webkit-slider-thumb {
+  -webkit-appearance: none;
+  appearance: none;
+  width: 25px;
+  height: 25px;
+  border-radius: 50%;
+  background: #04AA6D;
+  cursor: pointer;
+}
+
+.slider::-moz-range-thumb {
+  width: 25px;
+  height: 25px;
+  border-radius: 50%;
+  background: #04AA6D;
+  cursor: pointer;
+}
+
 #body::-webkit-scrollbar {
 #  display:none
 #}
diff --git a/scripts/advanced.php b/scripts/advanced.php
index f3859df..87c1f89 100644
--- a/scripts/advanced.php
+++ b/scripts/advanced.php
@@ -111,12 +111,7 @@ if(isset($_GET['submit'])) {
 
   if(isset($_GET["privacy_threshold"])) {
     $privacy_threshold = $_GET["privacy_threshold"];
-    if(strcmp($config['PRIVACY_THRESHOLD'], "1") == 0 ) {
-      $pmode = "on";
-    }elseif(strcmp($config['PRIVACY_THRESHOLD'], "") == 0) {
-      $pmode = "off";
-    }
-    if(strcmp($privacy_threshold,$pmode) !== 0) {
+    if(strcmp($privacy_threshold,$config['PRIVACY_THRESHOLD']) !== 0) {
       $contents = preg_replace("/PRIVACY_THRESHOLD=.*/", "PRIVACY_THRESHOLD=$privacy_threshold", $contents);
       $contents2 = preg_replace("/PRIVACY_THRESHOLD=.*/", "PRIVACY_THRESHOLD=$privacy_threshold", $contents2);
     }
@@ -185,12 +180,12 @@ if (file_exists('./scripts/thisrun.txt')) {
     <form action="" method="GET">
       <label>Privacy Threshold: </label><br>
       <div class="slidecontainer">
-        <input type="range" min="0" max="25" value="0" class="slider" id="myRange">
-        <p>Value: <span id="demo"></span>%</p>
+        <input name="privacy_threshold" type="range" min="0" max="25" value="<?php print($newconfig['PRIVACY_THRESHOLD']);?>" class="slider" id="privacy_threshold">
+        <p>Value: <span id="threshold_value"></span>%</p>
       </div>
       <script>
-      var slider = document.getElementById("myRange");
-      var output = document.getElementById("demo");
+      var slider = document.getElementById("privacy_threshold");
+      var output = document.getElementById("threshold_value");
       output.innerHTML = slider.value; // Display the default slider value
       
       // Update the current slider value (each time you drag the slider handle)
diff --git a/scripts/privacy_server.py b/scripts/privacy_server.py
deleted file mode 100755
index a103fff..0000000
--- a/scripts/privacy_server.py
+++ /dev/null
@@ -1,456 +0,0 @@
-import socket 
-import threading
-import os
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
-os.environ['CUDA_VISIBLE_DEVICES'] = ''
-
-try:
-    import tflite_runtime.interpreter as tflite
-except:
-    from tensorflow import lite as tflite
-
-import argparse
-import operator
-import librosa
-import numpy as np
-import math
-import time
-from decimal import Decimal
-import json
-import requests
-import sqlite3
-import datetime
-from time import sleep
-import pytz
-from tzlocal import get_localzone
-from pathlib import Path
-
-
-HEADER = 64
-PORT = 5050
-SERVER = socket.gethostbyname(socket.gethostname())
-ADDR = (SERVER, PORT)
-FORMAT = 'utf-8'
-DISCONNECT_MESSAGE = "!DISCONNECT"
-
-server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
-try:
-    server.bind(ADDR)
-except:
-    print("Waiting on socket")
-    time.sleep(5)
-    
-
-
-# Open most recent Configuration and grab DB_PWD as a python variable
-userDir = os.path.expanduser('~')
-with open(userDir + '/BirdNET-Pi/scripts/thisrun.txt', 'r') as f:
-    this_run = f.readlines()
-    audiofmt = "." + str(str(str([i for i in this_run if i.startswith('AUDIOFMT')]).split('=')[1]).split('\\')[0])
-
-
-def loadModel():
-
-    global INPUT_LAYER_INDEX
-    global OUTPUT_LAYER_INDEX
-    global MDATA_INPUT_INDEX
-    global CLASSES
-
-    print('LOADING TF LITE MODEL...', end=' ')
-
-    # Load TFLite model and allocate tensors.
-    modelpath = userDir + '/BirdNET-Pi/model/BirdNET_6K_GLOBAL_MODEL.tflite'
-    myinterpreter = tflite.Interpreter(model_path=modelpath,num_threads=2)
-    myinterpreter.allocate_tensors()
-
-    # Get input and output tensors.
-    input_details = myinterpreter.get_input_details()
-    output_details = myinterpreter.get_output_details()
-
-    # Get input tensor index
-    INPUT_LAYER_INDEX = input_details[0]['index']
-    MDATA_INPUT_INDEX = input_details[1]['index']
-    OUTPUT_LAYER_INDEX = output_details[0]['index']
-
-    # Load labels
-    CLASSES = []
-    with open(userDir + '/BirdNET-Pi/model/labels.txt', 'r') as lfile:
-        for line in lfile.readlines():
-            CLASSES.append(line.replace('\n', ''))
-
-    print('DONE!')
-
-    return myinterpreter
-
-def loadCustomSpeciesList(path):
-
-    slist = []
-    if os.path.isfile(path):
-        with open(path, 'r') as csfile:
-            for line in csfile.readlines():
-                slist.append(line.replace('\r', '').replace('\n', ''))
-
-    return slist
-
-def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5):
-
-    # Split signal with overlap
-    sig_splits = []
-    for i in range(0, len(sig), int((seconds - overlap) * rate)):
-        split = sig[i:i + int(seconds * rate)]
-
-        # End of signal?
-        if len(split) < int(minlen * rate):
-            break
-        
-        # Signal chunk too short? Fill with zeros.
-        if len(split) < int(rate * seconds):
-            temp = np.zeros((int(rate * seconds)))
-            temp[:len(split)] = split
-            split = temp
-        
-        sig_splits.append(split)
-
-    return sig_splits
-
-def readAudioData(path, overlap, sample_rate=48000):
-
-    print('READING AUDIO DATA...', end=' ', flush=True)
-
-    # Open file with librosa (uses ffmpeg or libav)
-    sig, rate = librosa.load(path, sr=sample_rate, mono=True, res_type='kaiser_fast')
-
-    # Split audio into 3-second chunks
-    chunks = splitSignal(sig, rate, overlap)
-
-    print('DONE! READ', str(len(chunks)), 'CHUNKS.')
-
-    return chunks
-
-def convertMetadata(m):
-
-    # Convert week to cosine
-    if m[2] >= 1 and m[2] <= 48:
-        m[2] = math.cos(math.radians(m[2] * 7.5)) + 1 
-    else:
-        m[2] = -1
-
-    # Add binary mask
-    mask = np.ones((3,))
-    if m[0] == -1 or m[1] == -1:
-        mask = np.zeros((3,))
-    if m[2] == -1:
-        mask[2] = 0.0
-
-    return np.concatenate([m, mask])
-
-def custom_sigmoid(x, sensitivity=1.0):
-    return 1 / (1.0 + np.exp(-sensitivity * x))
-
-def predict(sample, sensitivity):
-    global INTERPRETER
-    # Make a prediction
-    INTERPRETER.set_tensor(INPUT_LAYER_INDEX, np.array(sample[0], dtype='float32'))
-    INTERPRETER.set_tensor(MDATA_INPUT_INDEX, np.array(sample[1], dtype='float32'))
-    INTERPRETER.invoke()
-    prediction = INTERPRETER.get_tensor(OUTPUT_LAYER_INDEX)[0]
-
-    # Apply custom sigmoid
-    p_sigmoid = custom_sigmoid(prediction, sensitivity)
-
-    # Get label and scores for pooled predictions
-    p_labels = dict(zip(CLASSES, p_sigmoid))
-
-    # Sort by score
-    p_sorted = sorted(p_labels.items(), key=operator.itemgetter(1), reverse=True)
-
-    # Remove species that are on blacklist
-    for i in range(min(10, len(p_sorted))):
-        if p_sorted[i][0] in ['Non-bird_Non-bird', 'Noise_Noise']:
-            p_sorted[i] = (p_sorted[i][0], 0.0)
-        if p_sorted[i][0]=='Human_Human':
-            print("HUMAN SCORE:",str(p_sorted[i]))
-            HUMAN_FLAG=True
-            with open(userDir + '/BirdNET-Pi/HUMAN.txt', 'a') as rfile:
-                rfile.write(str(datetime.datetime.now())+str(p_sorted[i])+ '\n')
-#             date_stamp=datetime.datetime.now().strftime("%d_%m_%y_%H:%M:%S")
-# 
-#             sf.write('./home/*/human_sample.wav',np.random.randn(10,2) , 44100) #sample[0]
-
-    # Only return first the top ten results
-    #INCREASE THIS TO SEE IF HUMAN IS DETECTED MORE RELIABLY
-#    print('P_SORTED-------', p_sorted)
-    return p_sorted[:100]
-
-def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap,):
-    global INTERPRETER
-
-    detections = {}
-    start = time.time()
-    print('ANALYZING AUDIO...', end=' ', flush=True)
-
-    # Convert and prepare metadata
-    mdata = convertMetadata(np.array([lat, lon, week]))
-    mdata = np.expand_dims(mdata, 0)
-
-    # Parse every chunk
-    pred_start = 0.0
-    for c in chunks:
-
-        # Prepare as input signal
-        sig = np.expand_dims(c, 0)
-
-        # Make prediction
-        p = predict([sig, mdata], sensitivity)
-#        print("PPPPP",p)
-        HUMAN_DETECTED=False
-        #Catch if Human is recognized
-        for x in range(len(p)):
-            if "Human" in p[x][0]:
-#                print("HUMAN DETECTED!!",p[x][0])
-                #clear list
-                HUMAN_DETECTED=True
-                print("CHUNK -----",c)
-         
-        # Save result and timestamp
-        pred_end = pred_start + 3.0
-        
-        if HUMAN_DETECTED == True:
-            p=[('Human_Human',0.0)]*10
-            print("HUMAN DETECTED!!!",p)
-
-        detections[str(pred_start) + ';' + str(pred_end)] = p
-        
-        pred_start = pred_end - overlap
-
-    print('DONE! Time', int((time.time() - start) * 10) / 10.0, 'SECONDS')
-#    print('DETECTIONS:::::',detections)
-    return detections
-
-
-def writeResultsToFile(detections, min_conf, path):
-
-    print('WRITING RESULTS TO', path, '...', end=' ')
-    rcnt = 0
-    with open(path, 'w') as rfile:
-        rfile.write('Start (s);End (s);Scientific name;Common name;Confidence\n')
-        for d in detections:
-            for entry in detections[d]:
-                if entry[1] >= min_conf and ((entry[0] in INCLUDE_LIST or len(INCLUDE_LIST) == 0) and (entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0) ):
-                    rfile.write(d + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) + '\n')
-                    rcnt += 1
-    print('DONE! WROTE', rcnt, 'RESULTS.')
-    return
-
-def handle_client(conn, addr):
-    global INCLUDE_LIST
-    global EXCLUDE_LIST
-    print(f"[NEW CONNECTION] {addr} connected.")
-
-    connected = True
-    while connected:
-        msg_length = conn.recv(HEADER).decode(FORMAT)
-        if msg_length:
-            msg_length = int(msg_length)
-            msg = conn.recv(msg_length).decode(FORMAT)
-            if msg == DISCONNECT_MESSAGE:
-                connected = False
-            else:
-                #print(f"[{addr}] {msg}")
-                
-                args = type('', (), {})()
-                
-                args.i = ''
-                args.o = ''
-                args.birdweather_id = '99999'
-                args.include_list = 'null'
-                args.exclude_list = 'null'
-                args.overlap = 0.0
-                args.week = -1
-                args.sensitivity = 1.25
-                args.min_conf = 0.70
-                args.lat = -1
-                args.lon =  -1
-
-
-                for line in msg.split('||'):
-                    inputvars = line.split('=')
-                    if inputvars[0] == 'i':
-                        args.i = inputvars[1]
-                    elif inputvars[0] == 'o':
-                        args.o = inputvars[1]
-                    elif inputvars[0] == 'birdweather_id':
-                        args.birdweather_id = inputvars[1]
-                    elif inputvars[0] == 'include_list':
-                        args.include_list = inputvars[1]
-                    elif inputvars[0] == 'exclude_list':
-                        args.exclude_list = inputvars[1]
-                    elif inputvars[0] == 'overlap':
-                        args.overlap = float(inputvars[1])
-                    elif inputvars[0] == 'week':
-                        args.week = int(inputvars[1])
-                    elif inputvars[0] == 'sensitivity':
-                        args.sensitivity = float(inputvars[1])
-                    elif inputvars[0] == 'min_conf':
-                        args.min_conf = float(inputvars[1])
-                    elif inputvars[0] == 'lat':
-                        args.lat = float(inputvars[1])
-                    elif inputvars[0] == 'lon':
-                        args.lon = float(inputvars[1])
-
-
-                   
-                # Load custom species lists - INCLUDED and EXCLUDED
-                if not args.include_list == 'null':
-                    INCLUDE_LIST = loadCustomSpeciesList(args.include_list)
-                else:
-                    INCLUDE_LIST = []
-                
-                if not args.exclude_list == 'null':
-                    EXCLUDE_LIST = loadCustomSpeciesList(args.exclude_list)
-                else:
-                    EXCLUDE_LIST = []
-
-                birdweather_id = args.birdweather_id
-
-                # Read audio data
-                audioData = readAudioData(args.i, args.overlap)
-
-                # Get Date/Time from filename in case Pi gets behind
-                #now = datetime.now()
-                full_file_name = args.i
-                print('FULL FILENAME: -' + full_file_name + '-')
-                file_name = Path(full_file_name).stem
-                file_date = file_name.split('-birdnet-')[0]
-                file_time = file_name.split('-birdnet-')[1]
-                date_time_str = file_date + ' ' + file_time
-                date_time_obj = datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S')
-                #print('Date:', date_time_obj.date())
-                #print('Time:', date_time_obj.time())
-                print('Date-time:', date_time_obj)
-                now = date_time_obj
-                current_date = now.strftime("%Y-%m-%d")
-                current_time = now.strftime("%H:%M:%S")
-                current_iso8601 = now.astimezone(get_localzone()).isoformat()
-                
-                week_number = int(now.strftime("%V"))
-                week = max(1, min(week_number, 48))
-
-                sensitivity = max(0.5, min(1.0 - (args.sensitivity - 1.0), 1.5))
-
-                # Process audio data and get detections
-                detections = analyzeAudioData(audioData, args.lat, args.lon, week, sensitivity, args.overlap)
-
-                # Write detections to output file
-                min_conf = max(0.01, min(args.min_conf, 0.99))
-                writeResultsToFile(detections, min_conf, args.o)
-                
-            ###############################################################################    
-            ###############################################################################    
-                
-                soundscape_uploaded = False
-
-                # Write detections to Database
-                myReturn = ''
-                for i in detections:
-                  myReturn += str(i) + '-' + str(detections[i][0]) + '\n'
-                
-                
-                with open(userDir + '/BirdNET-Pi/BirdDB.txt', 'a') as rfile:
-                    for d in detections:
-                        for entry in detections[d]:
-                            if entry[1] >= min_conf and ((entry[0] in INCLUDE_LIST or len(INCLUDE_LIST) == 0) and (entry[0] not in EXCLUDE_LIST or len(EXCLUDE_LIST) == 0) ):
-                                rfile.write(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';' \
-                                + str(entry[1]) +";" + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';' \
-                                + str(args.sensitivity) +';' + str(args.overlap) + '\n')
-                                
-                                Date = str(current_date)
-                                Time = str(current_time)
-                                species = entry[0]
-                                Sci_Name,Com_Name = species.split('_')
-                                score = entry[1]
-                                Confidence = str(round(score*100))
-                                Lat = str(args.lat)
-                                Lon = str(args.lon)
-                                Cutoff = str(args.min_conf)
-                                Week = str(args.week)
-                                Sens = str(args.sensitivity)
-                                Overlap = str(args.overlap)
-                                Com_Name = Com_Name.replace("'", "")
-                                File_Name = Com_Name.replace(" ", "_") + '-' + Confidence + '-' + \
-                                        Date.replace("/", "-") + '-birdnet-' + Time + audiofmt
-
-                                #Connect to SQLite Database
-                                try: 
-                                    con = sqlite3.connect(userDir + '/BirdNET-Pi/scripts/birds.db')
-                                    cur = con.cursor()
-                                    cur.execute("INSERT INTO detections VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", (Date, Time, Sci_Name, Com_Name, str(score), Lat, Lon, Cutoff, Week, Sens, Overlap, File_Name))
-
-                                    con.commit()
-                                    con.close()
-                                except:
-                                    print("Database busy")
-                                    time.sleep(2)
-                                print(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) + ';' + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';' + str(args.sensitivity) +';' + str(args.overlap) + Com_Name.replace(" ", "_") + '-' + str(score) + '-' + str(current_date) + '-birdnet-' + str(current_time) + audiofmt  + '\n')
-
-                                if birdweather_id != "99999":
-                                    try:
-
-                                        if soundscape_uploaded is False:
-                                            # POST soundscape to server
-                                            soundscape_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id +  "/soundscapes" + "?timestamp=" + current_iso8601
-    
-                                            with open(args.i, 'rb') as f:
-                                                wav_data = f.read()
-                                            response = requests.post(url=soundscape_url, data=wav_data, headers={'Content-Type': 'application/octet-stream'})
-                                            print("Soundscape POST Response Status - ", response.status_code)
-                                            sdata = response.json()
-                                            soundscape_id = sdata['soundscape']['id']
-                                            soundscape_uploaded = True
-    
-                                        # POST detection to server
-                                        detection_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id + "/detections"
-                                        start_time = d.split(';')[0]
-                                        end_time = d.split(';')[1]
-                                        post_begin = "{ "
-                                        now_p_start = now + datetime.timedelta(seconds=float(start_time))
-                                        current_iso8601 = now_p_start.astimezone(get_localzone()).isoformat()
-                                        post_timestamp =  "\"timestamp\": \"" + current_iso8601 + "\","
-                                        post_lat = "\"lat\": " + str(args.lat) + ","
-                                        post_lon = "\"lon\": " + str(args.lon) + ","
-                                        post_soundscape_id = "\"soundscapeId\": " + str(soundscape_id) + ","
-                                        post_soundscape_start_time = "\"soundscapeStartTime\": " + start_time + ","
-                                        post_soundscape_end_time = "\"soundscapeEndTime\": " + end_time + ","
-                                        post_commonName = "\"commonName\": \"" + entry[0].split('_')[1] + "\","
-                                        post_scientificName = "\"scientificName\": \"" + entry[0].split('_')[0] + "\","
-                                        post_algorithm = "\"algorithm\": " + "\"alpha\"" + ","
-                                        post_confidence = "\"confidence\": " + str(entry[1])
-                                        post_end = " }"
-    
-                                        post_json = post_begin + post_timestamp + post_lat + post_lon + post_soundscape_id + post_soundscape_start_time + post_soundscape_end_time + post_commonName + post_scientificName + post_algorithm + post_confidence + post_end
-                                        print(post_json)
-                                        response = requests.post(detection_url, json=json.loads(post_json))
-                                        print("Detection POST Response Status - ", response.status_code)
-                                    except:
-                                        print("Cannot POST right now")
-                conn.send(myReturn.encode(FORMAT))
-
-                                #time.sleep(3)
-
-    conn.close() 
-
-def start():
-    # Load model
-    global INTERPRETER, INCLUDE_LIST, EXCLUDE_LIST
-    INTERPRETER = loadModel()
-    server.listen()
-    print(f"[LISTENING] Server is listening on {SERVER}")
-    while True:
-        conn, addr = server.accept()
-        thread = threading.Thread(target=handle_client, args=(conn, addr))
-        thread.start()
-        print(f"[ACTIVE CONNECTIONS] {threading.activeCount() - 1}")
-
-
-print("[STARTING] server is starting...")
-start()
diff --git a/scripts/update_birdnet_snippets.sh b/scripts/update_birdnet_snippets.sh
index 3c45174..7a2790d 100755
--- a/scripts/update_birdnet_snippets.sh
+++ b/scripts/update_birdnet_snippets.sh
@@ -9,8 +9,12 @@ if ! grep python3 <(head -n1 $my_dir/analyze.py) &>/dev/null;then
   echo "Ensure all python scripts use the virtual environment"
   sudo -u$USER sed -si "1 i\\#\!$HOME/BirdNET-Pi/birdnet/bin/python3" $my_dir/*.py
 fi
-if ! grep PRIVACY_MODE /etc/birdnet/birdnet.conf &>/dev/null;then
-  sudo -u$USER echo "PRIVACY_MODE=off" >> /etc/birdnet/birdnet.conf
+if ! grep PRIVACY_THRESHOLD /etc/birdnet/birdnet.conf &>/dev/null;then
+  sudo -u$USER echo "PRIVACY_THRESHOLD=0" >> /etc/birdnet/birdnet.conf
+fi
+if grep privacy ~/BirdNET-Pi/templates/birdnet_server.service &>/dev/null;then
+  sudo -E sed -i 's/privacy_server.py/server.py/g' \
+    ~/BirdNET-Pi/templates/birdnet_server.service
 fi
 if ! which lsof &>/dev/null;then
   sudo apt update && sudo apt -y install lsof