diff --git a/application_events.json b/application_events.json
index 999d3bc..bf489d5 100644
--- a/application_events.json
+++ b/application_events.json
@@ -1,5928 +1,5 @@
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+      "event_type": "performance_report",
+      "message": "Performance report: 118 points saved, 0 lost, 0.5% CPU",
+      "details": {
+        "duration": 10.031207084655762,
+        "points_saved": 118,
+        "points_rate": 11.763290200687685,
+        "variables_saved": 354,
+        "udp_points_sent": 0,
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+        "cpu_average": 0.5,
+        "cpu_max": 0.5,
+        "delay_average": 0.009728945218599759,
+        "delay_max": 0.02429366111755371,
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+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.07450079311758785,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:38:50.834732",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 118 points saved, 0 lost, 0.5% CPU",
+      "details": {
+        "duration": 10.032689571380615,
+        "points_saved": 118,
+        "points_rate": 11.761551990665433,
+        "variables_saved": 354,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.5,
+        "cpu_max": 0.5,
+        "delay_average": 0.008510971069335937,
+        "delay_max": 0.025498390197753906,
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+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.06993976083852477,
+        "csv_write_time_avg": 1.0546991380594544e-06
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:39:00.862993",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 118 points saved, 0 lost, 0.0% CPU",
+      "details": {
+        "duration": 10.028261423110962,
+        "points_saved": 118,
+        "points_rate": 11.766745502671,
+        "variables_saved": 354,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.0,
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+        "delay_average": 0.008485972881317139,
+        "delay_max": 0.029614686965942383,
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+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.07137028645660917,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:39:10.890639",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 117 points saved, 0 lost, 0.2% CPU",
+      "details": {
+        "duration": 10.026661396026611,
+        "points_saved": 117,
+        "points_rate": 11.668889112617789,
+        "variables_saved": 351,
+        "udp_points_sent": 0,
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+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.07813407824589656,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:39:20.921037",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 117 points saved, 0 lost, 0.0% CPU",
+      "details": {
+        "duration": 10.030382871627808,
+        "points_saved": 117,
+        "points_rate": 11.664559717949464,
+        "variables_saved": 351,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.0,
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+        "delay_average": 0.012426086094068445,
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+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.08023876002711108,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:39:30.950553",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 118 points saved, 0 lost, 0.2% CPU",
+      "details": {
+        "duration": 10.030515432357788,
+        "points_saved": 118,
+        "points_rate": 11.764101336142677,
+        "variables_saved": 354,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.2,
+        "cpu_max": 0.2,
+        "delay_average": 0.0073184967041015625,
+        "delay_max": 0.029512643814086914,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.07657499838683565,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:39:40.978793",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 119 points saved, 0 lost, 0.0% CPU",
+      "details": {
+        "duration": 10.028239965438843,
+        "points_saved": 119,
+        "points_rate": 11.866489075861725,
+        "variables_saved": 357,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.0,
+        "cpu_max": 0.0,
+        "delay_average": 0.004678355322943794,
+        "delay_max": 0.008371114730834961,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.07224507291777794,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:39:51.009913",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 118 points saved, 0 lost, 0.2% CPU",
+      "details": {
+        "duration": 10.03112006187439,
+        "points_saved": 118,
+        "points_rate": 11.763392250531076,
+        "variables_saved": 354,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.2,
+        "cpu_max": 0.2,
+        "delay_average": 0.010142660140991211,
+        "delay_max": 0.022010326385498047,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.06788122653961182,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:40:01.038417",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 117 points saved, 0 lost, 0.2% CPU",
+      "details": {
+        "duration": 10.027502536773682,
+        "points_saved": 117,
+        "points_rate": 11.667910286826453,
+        "variables_saved": 351,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.2,
+        "cpu_max": 0.2,
+        "delay_average": 0.012786799006991915,
+        "delay_max": 0.03872394561767578,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.0712335456130851,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:40:11.071447",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 115 points saved, 0 lost, 0.0% CPU",
+      "details": {
+        "duration": 10.033040761947632,
+        "points_saved": 115,
+        "points_rate": 11.46212825489169,
+        "variables_saved": 345,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.0,
+        "cpu_max": 0.0,
+        "delay_average": 0.016032307236282912,
+        "delay_max": 0.0527651309967041,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.0850260879682458,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:40:21.099096",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 115 points saved, 0 lost, 0.0% CPU",
+      "details": {
+        "duration": 10.028639554977417,
+        "points_saved": 115,
+        "points_rate": 11.467158568175199,
+        "variables_saved": 345,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.0,
+        "cpu_max": 0.0,
+        "delay_average": 0.013467006385326385,
+        "delay_max": 0.04805254936218262,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.08903484551802926,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:40:31.127939",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 115 points saved, 0 lost, 0.2% CPU",
+      "details": {
+        "duration": 10.027847290039062,
+        "points_saved": 115,
+        "points_rate": 11.46806454803442,
+        "variables_saved": 345,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.2,
+        "cpu_max": 0.2,
+        "delay_average": 0.011025435394710965,
+        "delay_max": 0.037154436111450195,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.08961239275724991,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:40:41.160448",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 116 points saved, 0 lost, 0.3% CPU",
+      "details": {
+        "duration": 10.033504724502563,
+        "points_saved": 116,
+        "points_rate": 11.56126430246446,
+        "variables_saved": 348,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.3,
+        "cpu_max": 0.3,
+        "delay_average": 0.012032093825163665,
+        "delay_max": 0.037841796875,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.0860556857339267,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:40:51.192774",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 119 points saved, 0 lost, 0.0% CPU",
+      "details": {
+        "duration": 10.032326221466064,
+        "points_saved": 119,
+        "points_rate": 11.861655748930586,
+        "variables_saved": 357,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.0,
+        "cpu_max": 0.0,
+        "delay_average": 0.005008050373622349,
+        "delay_max": 0.025420188903808594,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.07409250435708951,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:01.226299",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 118 points saved, 0 lost, 0.2% CPU",
+      "details": {
+        "duration": 10.032536029815674,
+        "points_saved": 118,
+        "points_rate": 11.761731993716847,
+        "variables_saved": 354,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.2,
+        "cpu_max": 0.2,
+        "delay_average": 0.009503761927286783,
+        "delay_max": 0.023630857467651367,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.0753347065489171,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:01.594450",
+      "level": "info",
+      "event_type": "config_reload",
+      "message": "Dataset configuration reloaded from files with CSV header validation",
+      "details": {
+        "datasets_count": 3,
+        "active_datasets_count": 3,
+        "csv_recording_active": true
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:11.261908",
+      "level": "info",
+      "event_type": "performance_report",
+      "message": "Performance report: 115 points saved, 0 lost, 0.5% CPU",
+      "details": {
+        "duration": 10.035540580749512,
+        "points_saved": 115,
+        "points_rate": 11.45927307798412,
+        "variables_saved": 345,
+        "udp_points_sent": 0,
+        "points_lost": 0,
+        "cpu_average": 0.5,
+        "cpu_max": 0.5,
+        "delay_average": 0.01338486318235044,
+        "delay_max": 0.04090261459350586,
+        "read_errors": 0,
+        "csv_errors": 0,
+        "udp_errors": 0,
+        "read_time_avg": 0.082755940893422,
+        "csv_write_time_avg": 0.0
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:21.299747",
+      "level": "info",
+      "event_type": "csv_recording_stopped",
+      "message": "🔥 CRITICAL: CSV recording stopped (dataset threads continue for UDP streaming)",
+      "details": {
+        "recording_protection": false,
+        "performance_monitoring": false
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:21.339241",
+      "level": "info",
+      "event_type": "udp_streaming_stopped",
+      "message": "UDP streaming to PlotJuggler stopped (CSV recording continues)",
+      "details": {}
+    },
+    {
+      "timestamp": "2025-08-17T11:41:21.425370",
+      "level": "info",
+      "event_type": "dataset_deactivated",
+      "message": "Dataset deactivated: Fast",
+      "details": {
+        "dataset_id": "Fast"
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:21.455998",
+      "level": "info",
+      "event_type": "dataset_deactivated",
+      "message": "Dataset deactivated: test",
+      "details": {
+        "dataset_id": "Test"
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:21.753903",
+      "level": "info",
+      "event_type": "dataset_deactivated",
+      "message": "Dataset deactivated: DAR",
+      "details": {
+        "dataset_id": "DAR"
+      }
+    },
+    {
+      "timestamp": "2025-08-17T11:41:21.786104",
+      "level": "info",
+      "event_type": "plc_disconnection",
+      "message": "Disconnected from PLC 10.1.33.11 (manually disconnected)",
+      "details": {}
     }
   ],
-  "last_updated": "2025-08-17T11:00:20.886688",
+  "last_updated": "2025-08-17T11:41:21.786104",
   "total_entries": 1000
 }
\ No newline at end of file
diff --git a/config/data/dataset_definitions.json b/config/data/dataset_definitions.json
index 8a1f05b..452afe4 100644
--- a/config/data/dataset_definitions.json
+++ b/config/data/dataset_definitions.json
@@ -14,7 +14,7 @@
       "id": "Fast",
       "name": "Fast",
       "prefix": "fast",
-      "sampling_interval": 0.1
+      "sampling_interval": 0.5
     },
     {
       "enabled": true,
diff --git a/config/data/dataset_variables.json b/config/data/dataset_variables.json
index 97f06a8..3f991b9 100644
--- a/config/data/dataset_variables.json
+++ b/config/data/dataset_variables.json
@@ -36,20 +36,29 @@
       "dataset_id": "Fast",
       "variables": [
         {
-          "area": "db",
           "configType": "symbol",
+          "area": "db",
           "streaming": true,
-          "symbol": "AUX Blink_1.0S",
+          "symbol": "AUX Blink_2.0S",
           "type": "real"
         },
         {
-          "area": "m",
-          "bit": 6,
           "configType": "manual",
-          "name": "AUX Blink_1.6S",
-          "offset": 0,
-          "streaming": true,
+          "area": "m",
+          "bit": 1,
+          "name": "M50.1",
+          "offset": 50,
+          "streaming": false,
           "type": "bool"
+        },
+        {
+          "configType": "manual",
+          "area": "m",
+          "type": "bool",
+          "streaming": false,
+          "offset": 50,
+          "bit": 2,
+          "name": "M50.2"
         }
       ]
     }
diff --git a/config/data/plot_definitions.json b/config/data/plot_definitions.json
index 862cd9c..eb5be7e 100644
--- a/config/data/plot_definitions.json
+++ b/config/data/plot_definitions.json
@@ -8,7 +8,7 @@
       "point_radius": 2.5,
       "stacked": true,
       "stepped": true,
-      "time_window": 36,
+      "time_window": 10,
       "trigger_enabled": false,
       "trigger_on_true": true,
       "trigger_variable": null,
diff --git a/config/data/plot_variables.json b/config/data/plot_variables.json
index 3b7122f..71c9565 100644
--- a/config/data/plot_variables.json
+++ b/config/data/plot_variables.json
@@ -4,34 +4,27 @@
       "plot_id": "plot_1",
       "variables": [
         {
-          "variable_name": "UR29_Brix",
+          "color": "#3498db",
+          "enabled": true,
           "label": "Brix",
-          "color": "#3498db",
           "line_width": 2,
-          "y_axis": "left",
-          "enabled": true
+          "variable_name": "UR29_Brix",
+          "y_axis": "left"
         },
         {
-          "variable_name": "UR29_ma",
-          "label": "ma",
           "color": "#dce740",
+          "enabled": true,
+          "label": "ma",
           "line_width": 2,
-          "y_axis": "left",
-          "enabled": true
+          "variable_name": "UR29_ma",
+          "y_axis": "left"
         },
         {
-          "variable_name": "AUX Blink_1.0S",
           "color": "#3498db",
+          "enabled": true,
           "line_width": 2,
-          "y_axis": "right",
-          "enabled": true
-        },
-        {
-          "variable_name": "AUX Blink_1.6S",
-          "color": "#630de3",
-          "line_width": 2,
-          "y_axis": "right",
-          "enabled": true
+          "variable_name": "AUX Blink_2.0S",
+          "y_axis": "right"
         }
       ]
     },
@@ -39,18 +32,25 @@
       "plot_id": "Clock",
       "variables": [
         {
-          "color": "#3498db",
-          "enabled": true,
+          "variable_name": "AUX Blink_2.0S",
+          "color": "#db3376",
           "line_width": 2,
-          "variable_name": "AUX Blink_1.0S",
-          "y_axis": "left"
+          "y_axis": "left",
+          "enabled": true
         },
         {
-          "color": "#87db33",
-          "enabled": true,
+          "variable_name": "M50.1",
+          "color": "#3498db",
           "line_width": 2,
-          "variable_name": "AUX Blink_1.6S",
-          "y_axis": "left"
+          "y_axis": "left",
+          "enabled": true
+        },
+        {
+          "variable_name": "M50.2",
+          "color": "#3edb33",
+          "line_width": 2,
+          "y_axis": "left",
+          "enabled": true
         }
       ]
     }
diff --git a/core/plc_client.py b/core/plc_client.py
index f52f98d..60bef1e 100644
--- a/core/plc_client.py
+++ b/core/plc_client.py
@@ -38,8 +38,9 @@ class PLCClient:
         # Global I/O serialization to avoid concurrent snap7 calls
         # Acts as a simple read queue to prevent 'CLI : Job pending'
         self.io_lock = threading.RLock()
-        # Small inter-read delay to give PLC time between requests (seconds)
-        self.inter_read_delay_seconds = 0.002
+        # 🚨 CRITICAL FIX: Increased inter-read delay for industrial PLC stability
+        # Original 0.002s was too aggressive, causing timing issues and lost points
+        self.inter_read_delay_seconds = 0.01  # 10ms between reads for stability
 
     def connect(self, ip: str, rack: int, slot: int) -> bool:
         """Connect to S7-315 PLC"""
@@ -281,7 +282,13 @@ class PLCClient:
                     "md",
                     "mb",
                 ]:  # Memory Word, Memory, Memory Double, Memory Byte
-                    result = self._read_memory_variable(offset, var_type)
+                    # 🚨 CRITICAL FIX: Handle memory bit reads correctly
+                    if var_type == "bool" and bit is not None:
+                        # Specific bit read (e.g., M50.1, M50.2, etc.)
+                        result = self._read_memory_bit(offset, bit)
+                    else:
+                        # Standard memory variable read
+                        result = self._read_memory_variable(offset, var_type)
                 elif area_type in [
                     "pew",
                     "pe",
@@ -307,7 +314,7 @@ class PLCClient:
                         self.logger.error(f"Unsupported area type: {area_type}")
                     result = None
 
-                # Small pacing delay between PLC I/O to avoid job overlap
+                # 🚨 CRITICAL: Increased pacing delay for industrial PLC stability
                 if self.inter_read_delay_seconds and self.inter_read_delay_seconds > 0:
                     time.sleep(self.inter_read_delay_seconds)
 
@@ -346,6 +353,201 @@ class PLCClient:
 
                 return None
 
+    def read_variables_batch(
+        self, variables_config: Dict[str, Dict[str, Any]]
+    ) -> Dict[str, Any]:
+        """🚨 NEW: Read multiple variables in optimized batch operations to reduce snap7 calls
+
+        Args:
+            variables_config: Dict of {var_name: var_config}
+
+        Returns:
+            Dict of {var_name: value} or {var_name: None} if read failed
+
+        This method groups variables by DB/Area and performs batch reads when possible,
+        significantly reducing the number of snap7 calls and improving timing performance.
+        """
+        if not self.is_connected():
+            return {name: None for name in variables_config.keys()}
+
+        results = {}
+
+        # Ensure only one snap7 operation at a time
+        with self.io_lock:
+            try:
+                # Group variables by area and DB for batch reading
+                groups = self._group_variables_for_batch_reading(variables_config)
+
+                for group_key, var_group in groups.items():
+                    area_type, db_number = group_key
+
+                    if area_type == "db" and len(var_group) > 1:
+                        # Batch read for DB variables
+                        batch_results = self._batch_read_db_variables(
+                            db_number, var_group
+                        )
+                        results.update(batch_results)
+                    else:
+                        # Fall back to individual reads for non-batchable variables
+                        for var_name, var_config in var_group.items():
+                            results[var_name] = self.read_variable(var_config)
+
+                return results
+
+            except Exception as e:
+                if self.logger:
+                    self.logger.error(f"Error in batch read operation: {e}")
+
+                # Fall back to individual reads if batch fails
+                for var_name, var_config in variables_config.items():
+                    results[var_name] = self.read_variable(var_config)
+
+                return results
+
+    def _group_variables_for_batch_reading(
+        self, variables_config: Dict[str, Dict[str, Any]]
+    ) -> Dict[tuple, Dict[str, Dict[str, Any]]]:
+        """Group variables by area and DB for efficient batch reading"""
+        groups = {}
+
+        for var_name, var_config in variables_config.items():
+            area_type = var_config.get("area", "db").lower()
+            db_number = var_config.get("db", None)
+
+            # Create group key
+            group_key = (area_type, db_number)
+
+            if group_key not in groups:
+                groups[group_key] = {}
+
+            groups[group_key][var_name] = var_config
+
+        return groups
+
+    def _batch_read_db_variables(
+        self, db_number: int, variables: Dict[str, Dict[str, Any]]
+    ) -> Dict[str, Any]:
+        """Perform optimized batch read for DB variables in the same data block"""
+        if not variables:
+            return {}
+
+        results = {}
+
+        try:
+            # Find min and max offsets to determine read range
+            offsets = []
+            for var_config in variables.values():
+                offset = var_config.get("offset", 0)
+                var_type = var_config.get("type", "real").lower()
+
+                # Calculate size based on type
+                type_sizes = {
+                    "real": 4,
+                    "dint": 4,
+                    "int": 2,
+                    "bool": 1,
+                    "word": 2,
+                    "byte": 1,
+                    "uint": 2,
+                    "udint": 4,
+                    "sint": 1,
+                    "usint": 1,
+                }
+                size = type_sizes.get(var_type, 4)
+
+                offsets.append((offset, offset + size))
+
+            if not offsets:
+                return results
+
+            # Calculate optimal read range
+            min_offset = min(start for start, end in offsets)
+            max_offset = max(end for start, end in offsets)
+            read_size = max_offset - min_offset
+
+            # If range is reasonable (< 256 bytes), do single batch read
+            if read_size <= 256 and len(variables) > 1:
+                raw_data = self.plc.db_read(db_number, min_offset, read_size)
+
+                # Extract individual variable values from the batch
+                for var_name, var_config in variables.items():
+                    try:
+                        offset = var_config.get("offset", 0)
+                        var_type = var_config.get("type", "real").lower()
+                        bit = var_config.get("bit")
+
+                        # Calculate relative offset in the batch
+                        relative_offset = offset - min_offset
+
+                        # Extract value based on type
+                        value = self._extract_value_from_batch(
+                            raw_data, relative_offset, var_type, bit
+                        )
+                        results[var_name] = value
+
+                    except Exception as e:
+                        if self.logger:
+                            self.logger.warning(
+                                f"Error extracting variable {var_name} from batch: {e}"
+                            )
+                        results[var_name] = None
+
+                # Single delay for the entire batch
+                if self.inter_read_delay_seconds > 0:
+                    time.sleep(self.inter_read_delay_seconds)
+
+            else:
+                # Range too large or single variable, fall back to individual reads
+                for var_name, var_config in variables.items():
+                    results[var_name] = self.read_variable(var_config)
+
+        except Exception as e:
+            if self.logger:
+                self.logger.warning(
+                    f"Batch read failed for DB{db_number}, falling back to individual reads: {e}"
+                )
+
+            # Fall back to individual reads
+            for var_name, var_config in variables.items():
+                results[var_name] = self.read_variable(var_config)
+
+        return results
+
+    def _extract_value_from_batch(
+        self, raw_data: bytes, offset: int, var_type: str, bit: Optional[int] = None
+    ) -> Any:
+        """Extract a specific variable value from batch read data"""
+        try:
+            if var_type == "real":
+                return struct.unpack(">f", raw_data[offset : offset + 4])[0]
+            elif var_type == "int":
+                return struct.unpack(">h", raw_data[offset : offset + 2])[0]
+            elif var_type == "bool":
+                if bit is not None:
+                    return snap7.util.get_bool(raw_data[offset : offset + 1], 0, bit)
+                else:
+                    return bool(raw_data[offset] & 0x01)
+            elif var_type == "dint":
+                return struct.unpack(">l", raw_data[offset : offset + 4])[0]
+            elif var_type == "word":
+                return struct.unpack(">H", raw_data[offset : offset + 2])[0]
+            elif var_type == "byte":
+                return struct.unpack(">B", raw_data[offset : offset + 1])[0]
+            elif var_type == "uint":
+                return struct.unpack(">H", raw_data[offset : offset + 2])[0]
+            elif var_type == "udint":
+                return struct.unpack(">L", raw_data[offset : offset + 4])[0]
+            elif var_type == "sint":
+                return struct.unpack(">b", raw_data[offset : offset + 1])[0]
+            elif var_type == "usint":
+                return struct.unpack(">B", raw_data[offset : offset + 1])[0]
+        except Exception as e:
+            if self.logger:
+                self.logger.warning(
+                    f"Error extracting {var_type} at offset {offset}: {e}"
+                )
+            return None
+
     def _read_db_variable(
         self, var_config: Dict[str, Any], offset: int, var_type: str, bit: Optional[int]
     ) -> Any:
diff --git a/core/streamer.py b/core/streamer.py
index 960c760..276df36 100644
--- a/core/streamer.py
+++ b/core/streamer.py
@@ -74,7 +74,15 @@ class DataStreamer:
         self.dataset_csv_hours = {}  # dataset_id -> current hour
         self.dataset_using_modification_files = {}  # dataset_id -> bool
 
-        # 📊 CACHE SYSTEM - Central data storage
+        # � NEW: Asynchronous CSV Writing System
+        # Buffer system to accumulate data and write in batches every 5 seconds
+        self.csv_buffer = {}  # dataset_id -> list of [timestamp, data_dict]
+        self.csv_buffer_lock = threading.Lock()
+        self.csv_flush_interval = 5.0  # seconds
+        self.csv_flush_thread = None
+        self.csv_flush_active = False
+
+        # �📊 CACHE SYSTEM - Central data storage
         # This is the ONLY source of data for all APIs and interfaces
         # Updated ONLY by read_dataset_variables() during streaming cycles
         self.last_read_values = {}  # dataset_id -> {var_name: value}
@@ -334,7 +342,7 @@ class DataStreamer:
                     )
 
     def write_dataset_csv_data(self, dataset_id: str, data: Dict[str, Any]):
-        """Write data to CSV file for a specific dataset"""
+        """🚨 DEPRECATED: Use buffer_dataset_csv_data instead for async writing"""
         if dataset_id not in self.config_manager.active_datasets:
             return
 
@@ -366,6 +374,119 @@ class DataStreamer:
                     f"Error writing CSV data for dataset {dataset_id}: {e}"
                 )
 
+    def buffer_dataset_csv_data(self, dataset_id: str, data: Dict[str, Any]):
+        """🚨 NEW: Buffer CSV data for asynchronous writing to reduce I/O operations"""
+        if dataset_id not in self.config_manager.active_datasets:
+            return
+
+        timestamp = datetime.now()
+        
+        with self.csv_buffer_lock:
+            if dataset_id not in self.csv_buffer:
+                self.csv_buffer[dataset_id] = []
+            
+            # Add data to buffer with timestamp
+            self.csv_buffer[dataset_id].append({
+                'timestamp': timestamp,
+                'data': data.copy()
+            })
+
+    def _csv_flush_loop(self):
+        """🚨 Background thread to flush CSV buffers every flush_interval seconds"""
+        while self.csv_flush_active:
+            try:
+                time.sleep(self.csv_flush_interval)
+                self._flush_csv_buffers()
+            except Exception as e:
+                if self.logger:
+                    self.logger.error(f"Error in CSV flush loop: {e}")
+
+    def _flush_csv_buffers(self):
+        """🚨 Flush all buffered CSV data to files"""
+        flush_start_time = time.time()
+        total_points_written = 0
+        datasets_flushed = 0
+        
+        with self.csv_buffer_lock:
+            for dataset_id, buffer_data in self.csv_buffer.items():
+                if not buffer_data:
+                    continue
+                    
+                try:
+                    self.setup_dataset_csv_file(dataset_id)
+                    
+                    if dataset_id in self.dataset_csv_writers:
+                        dataset_variables = self.config_manager.get_dataset_variables(dataset_id)
+                        
+                        for entry in buffer_data:
+                            timestamp_str = entry['timestamp'].strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]
+                            data = entry['data']
+                            
+                            # Create row with all variables for this dataset
+                            row = [timestamp_str]
+                            for var_name in dataset_variables.keys():
+                                value = data.get(var_name, None)
+                                # Convert boolean values to 0 or 1 for CSV consistency
+                                if isinstance(value, bool):
+                                    value = 1 if value else 0
+                                row.append(value)
+                            
+                            self.dataset_csv_writers[dataset_id].writerow(row)
+                            total_points_written += 1
+                        
+                        # Flush file to disk
+                        self.dataset_csv_files[dataset_id].flush()
+                        datasets_flushed += 1
+                        
+                except Exception as e:
+                    if self.logger:
+                        self.logger.error(f"Error flushing CSV buffer for dataset {dataset_id}: {e}")
+            
+            # Clear all buffers after successful flush
+            self.csv_buffer.clear()
+        
+        flush_time = time.time() - flush_start_time
+        
+        if total_points_written > 0 and self.logger:
+            # 🚨 FIX: Avoid division by zero when flush_time is 0
+            throughput = total_points_written / max(flush_time, 0.001)  # Minimum 1ms to avoid division by zero
+            self.logger.debug(
+                f"📝 CSV Batch Flush: {total_points_written} points written across {datasets_flushed} datasets "
+                f"in {flush_time:.3f}s ({throughput:.1f} points/sec)"
+            )
+
+    def start_csv_flush_thread(self):
+        """🚨 Start the asynchronous CSV flush thread"""
+        if self.csv_flush_active:
+            return
+            
+        self.csv_flush_active = True
+        self.csv_flush_thread = threading.Thread(
+            target=self._csv_flush_loop,
+            name="csv_flush_thread",
+            daemon=True
+        )
+        self.csv_flush_thread.start()
+        
+        if self.logger:
+            self.logger.info(f"📝 CSV async flush thread started (interval: {self.csv_flush_interval}s)")
+
+    def stop_csv_flush_thread(self):
+        """🚨 Stop the asynchronous CSV flush thread and flush remaining data"""
+        if not self.csv_flush_active:
+            return
+            
+        self.csv_flush_active = False
+        
+        # Final flush of any remaining data
+        self._flush_csv_buffers()
+        
+        if self.csv_flush_thread and self.csv_flush_thread.is_alive():
+            self.csv_flush_thread.join(timeout=5.0)
+            
+        if self.logger:
+            self.logger.info("📝 CSV async flush thread stopped, final flush completed")
+
     def create_new_dataset_csv_file_for_variable_modification(self, dataset_id: str):
         """Create a new CSV file for a dataset when variables are modified during active recording"""
         if dataset_id not in self.config_manager.active_datasets:
@@ -455,44 +576,92 @@ class DataStreamer:
 
         Called by: dataset_streaming_loop() at configured intervals
         Updates: self.last_read_values cache for use by all other functions
+        
+        🚨 CRITICAL FIX: Returns None if ANY variable fails - prevents corrupt CSV data
+        🚀 PERFORMANCE FIX: Uses batch reading to reduce snap7 calls and improve timing
         """
         data = {}
         errors = {}
         timestamp = datetime.now()
+        failed_variables = []
 
-        for var_name, var_config in variables.items():
-            try:
-                value = self.plc_client.read_variable(var_config)
-                data[var_name] = value
+        try:
+            # 🚀 NEW: Use batch reading for improved performance
+            batch_results = self.plc_client.read_variables_batch(variables)
+            
+            for var_name, value in batch_results.items():
+                if value is not None:
+                    data[var_name] = value
+                    
+                    # Clear any previous error for this variable
+                    if (
+                        dataset_id in self.last_read_errors
+                        and var_name in self.last_read_errors[dataset_id]
+                    ):
+                        del self.last_read_errors[dataset_id][var_name]
+                else:
+                    # Variable read failed
+                    var_config = variables.get(var_name, {})
+                    error_msg = f"Batch read failed for variable {var_name}"
+                    
+                    if self.logger:
+                        self.logger.warning(
+                            f"Error reading variable {var_name} in dataset {dataset_id}: {error_msg}"
+                        )
+                    data[var_name] = None
+                    errors[var_name] = error_msg
+                    failed_variables.append(var_name)
+        
+        except Exception as e:
+            # Fall back to individual reads if batch reading fails completely
+            if self.logger:
+                self.logger.warning(f"Batch reading failed for dataset {dataset_id}, falling back to individual reads: {e}")
+            
+            for var_name, var_config in variables.items():
+                try:
+                    value = self.plc_client.read_variable(var_config)
+                    data[var_name] = value
 
-                # Clear any previous error for this variable
-                if (
-                    dataset_id in self.last_read_errors
-                    and var_name in self.last_read_errors[dataset_id]
-                ):
-                    del self.last_read_errors[dataset_id][var_name]
+                    # Clear any previous error for this variable
+                    if (
+                        dataset_id in self.last_read_errors
+                        and var_name in self.last_read_errors[dataset_id]
+                    ):
+                        del self.last_read_errors[dataset_id][var_name]
 
-            except Exception as e:
-                if self.logger:
-                    self.logger.warning(
-                        f"Error reading variable {var_name} in dataset {dataset_id}: {e}"
-                    )
-                data[var_name] = None
-                errors[var_name] = f"Read error: {str(e)}"
+                except Exception as read_error:
+                    if self.logger:
+                        self.logger.warning(
+                            f"Error reading variable {var_name} in dataset {dataset_id}: {read_error}"
+                        )
+                    data[var_name] = None
+                    errors[var_name] = f"Read error: {str(read_error)}"
+                    failed_variables.append(var_name)
 
-        # Update cache with latest values and timestamp
-        self.last_read_values[dataset_id] = data.copy()
-        self.last_read_timestamps[dataset_id] = timestamp
-
-        # Update errors cache
-        if errors:
+        # 🚨 CRITICAL FIX: If ANY variable failed, return None to prevent CSV corruption
+        # This ensures that incomplete data is never written to CSV
+        if failed_variables:
+            if self.logger:
+                dataset_name = self.config_manager.datasets.get(dataset_id, {}).get('name', dataset_id)
+                self.logger.warning(
+                    f"🚨 CRITICAL: Dataset '{dataset_name}' read failed - {len(failed_variables)} variables failed: {failed_variables}. "
+                    f"Skipping CSV write to prevent data corruption."
+                )
+            # Still update cache for monitoring purposes, but return None for CSV
+            self.last_read_values[dataset_id] = data.copy()
+            self.last_read_timestamps[dataset_id] = timestamp
             if dataset_id not in self.last_read_errors:
                 self.last_read_errors[dataset_id] = {}
             self.last_read_errors[dataset_id].update(errors)
-        elif dataset_id in self.last_read_errors:
-            # Clear all errors if this read was completely successful
-            if all(value is not None for value in data.values()):
-                self.last_read_errors[dataset_id] = {}
+            return None
+
+        # Update cache with latest values and timestamp ONLY if all reads succeeded
+        self.last_read_values[dataset_id] = data.copy()
+        self.last_read_timestamps[dataset_id] = timestamp
+
+        # Clear all errors if this read was completely successful
+        if dataset_id in self.last_read_errors:
+            self.last_read_errors[dataset_id] = {}
 
         return data
 
@@ -635,29 +804,31 @@ class DataStreamer:
                     all_data = self.read_dataset_variables(dataset_id, dataset_variables)
                 
                 read_time = time.time() - read_start
-                read_success = bool(all_data)
+                # 🚨 CRITICAL FIX: Proper validation - all_data is None if ANY variable failed
+                read_success = all_data is not None
 
-                if all_data:
+                if all_data is not None:
                     consecutive_errors = 0
 
-                    # 📝 CSV Recording: ALWAYS FIRST - HIGHEST PRIORITY with timing
+                    # 📝 CSV Recording: ALWAYS FIRST - HIGHEST PRIORITY with ASYNC BUFFERING
                     if self.csv_recording_enabled:
                         csv_start = time.time()
                         try:
-                            self.write_dataset_csv_data(dataset_id, all_data)
+                            # 🚨 NEW: Use async buffering instead of immediate write
+                            self.buffer_dataset_csv_data(dataset_id, all_data)
                             csv_write_time = time.time() - csv_start
                             
-                            # 📊 Record successful CSV write
+                            # 📊 Record successful CSV buffer operation (much faster)
                             self.performance_monitor.record_csv_write(dataset_id, csv_write_time, success=True)
                             
                         except Exception as csv_error:
                             csv_write_time = time.time() - csv_start
                             
-                            # 📊 Record CSV write error
+                            # 📊 Record CSV buffer error
                             self.performance_monitor.record_csv_write(dataset_id, csv_write_time, success=False)
                             
                             if self.logger:
-                                self.logger.error(f"🚨 CSV WRITE ERROR for dataset '{dataset_info['name']}': {csv_error}")
+                                self.logger.error(f"🚨 CSV BUFFER ERROR for dataset '{dataset_info['name']}': {csv_error}")
 
                     # 📡 UDP Streaming: Lower priority - only if enabled
                     if self.udp_streaming_enabled:
@@ -673,7 +844,14 @@ class DataStreamer:
                         )
 
                 else:
+                    # 🚨 CRITICAL: All data read failed - increment error counter
                     consecutive_errors += 1
+                    if self.logger:
+                        self.logger.warning(
+                            f"🚨 CRITICAL: Dataset '{dataset_info['name']}' read completely failed. "
+                            f"No CSV data written to prevent corruption (consecutive errors: {consecutive_errors})"
+                        )
+                    
                     if consecutive_errors >= max_consecutive_errors:
                         self.event_logger.log_event(
                             "error",
@@ -940,6 +1118,9 @@ class DataStreamer:
         
         # 📊 START PERFORMANCE MONITORING
         self.performance_monitor.start_monitoring()
+        
+        # 🚨 START ASYNC CSV FLUSH THREAD
+        self.start_csv_flush_thread()
 
         # Activate all datasets that have variables for CSV recording
         activated_count = 0
@@ -974,21 +1155,26 @@ class DataStreamer:
         self.event_logger.log_event(
             "info",
             "csv_recording_started",
-            f"🔥 CRITICAL PRIORITY: CSV recording started with MAXIMUM PRIORITY and performance monitoring: {activated_count} datasets activated",
+            f"🔥 CRITICAL PRIORITY: CSV recording started with MAXIMUM PRIORITY, async buffering, and performance monitoring: {activated_count} datasets activated",
             {
                 "activated_datasets": activated_count,
                 "total_datasets": len(self.config_manager.datasets),
                 "priority": "CRITICAL",
                 "recording_protection": True,
-                "performance_monitoring": True
+                "performance_monitoring": True,
+                "async_csv_buffering": True,
+                "csv_flush_interval": self.csv_flush_interval
             },
         )
         return True
 
     def stop_csv_recording(self):
-        """🔥 CRITICAL: Stop CSV recording safely with performance monitoring"""
+        """🔥 CRITICAL: Stop CSV recording safely with performance monitoring and async flush"""
         self.csv_recording_enabled = False
         
+        # 🚨 STOP ASYNC CSV FLUSH THREAD AND FLUSH REMAINING DATA
+        self.stop_csv_flush_thread()
+        
         # 🔥 DISABLE RECORDING PROTECTION MODE
         self.recording_protector.stop_recording_protection()
         
@@ -1488,9 +1674,12 @@ class DataStreamer:
             # 1. Stop performance monitoring first
             self.performance_monitor.stop_monitoring()
             
-            # 2. Stop CSV recording first (graceful stop)
+            # 2. Stop CSV recording first (graceful stop with buffer flush)
             if self.csv_recording_enabled:
                 self.stop_csv_recording()
+            else:
+                # Ensure CSV flush thread is stopped even if recording wasn't active
+                self.stop_csv_flush_thread()
             
             # 3. Stop UDP streaming
             if self.udp_streaming_enabled:
diff --git a/frontend/src/components/ChartjsPlot.jsx b/frontend/src/components/ChartjsPlot.jsx
index 5fb5ec9..af6b780 100644
--- a/frontend/src/components/ChartjsPlot.jsx
+++ b/frontend/src/components/ChartjsPlot.jsx
@@ -55,7 +55,7 @@ const ChartjsPlot = ({ session, height = '400px' }) => {
         insertNaNOnNextIngest: false,
         isPaused: false,
         isRealTimeMode: true,
-        refreshRate: 1000,
+        refreshRate: 500,
         userOverrideUntil: 0,
         userPaused: false,
         sessionId: null
@@ -702,7 +702,7 @@ const ChartjsPlot = ({ session, height = '400px' }) => {
                             realtime: {
                                 duration: (config.time_window || 60) * 1000,
                                 refresh: sessionDataRef.current.refreshRate,
-                                delay: 0,
+                                delay: sessionDataRef.current.refreshRate,
                                 frameRate: 30,
                                 pause: !session.is_active || session.is_paused,
                                 onRefresh: (chart) => {
diff --git a/system_state.json b/system_state.json
index 24940b9..ca8afb0 100644
--- a/system_state.json
+++ b/system_state.json
@@ -1,12 +1,9 @@
 {
     "last_state": {
-        "should_connect": true,
+        "should_connect": false,
         "should_stream": false,
-        "active_datasets": [
-            "Fast",
-            "DAR"
-        ]
+        "active_datasets": []
     },
     "auto_recovery_enabled": true,
-    "last_update": "2025-08-17T10:48:18.548096"
+    "last_update": "2025-08-17T11:41:21.785119"
 }
\ No newline at end of file