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--- iothings:proiecte:2025sric:runtrack32 [2025/05/29 00:55]
alexandra.cornea01 [Software Design]
+++ iothings:proiecte:2025sric:runtrack32 [2025/05/29 02:31] (current)
alexandra.cornea01 [Demonstration and Results]
@@ Line 17: / Line 17: @@
 The sensors are powered via the breadboard's power rails, and communication is established using serial (for GPS) and I2C (for MAX30100).
-{{:iothings:proiecte:2025sric:runtracker.jpg?500|}}
+{{:iothings:proiecte:2025sric:runtracker.jpg?570|}}
 **GPS (Neo-6M) Connections**
@@ Line 169: / Line 169: @@
 === Mobile App Code ===
-==== Setup ====
+The Android application is built using Kotlin and connects to the ESP32 via Bluetooth to display real-time fitness data. Upon launch, the app searches for a bonded device named RunTracker32, establishes a Bluetooth socket connection, and listens for incoming data in a background thread.
-==== Results ====
+The ''listenForData()'' function reads Bluetooth messages, and once a newline character is detected, the message is passed to ''parseAndDisplay()''. This function uses regular expressions to extract values for heart rate (BPM), oxygen saturation (SpO₂), and GPS coordinates. These values are then shown in the app's user interface.
+<code>
+private fun listenForData() {
+  val input: InputStream? = bluetoothSocket?.inputStream
+  val buffer = ByteArray(1024)
+  val messageBuilder = StringBuilder()
+  while (true) {
+    val bytes = input?.read(buffer) ?: break
+    val readMessage = String(buffer, 0, bytes)
+    messageBuilder.append(readMessage)
+    if (readMessage.contains("\n")) {
+      val fullMessage = messageBuilder.toString().trim()
+      messageBuilder.clear()
+      runOnUiThread {
+        parseAndDisplay(fullMessage)
+      }
+    }
+  }
+}
+</code>
+<code>
+private fun parseAndDisplay(message: String) {
+  val bpmRegex = Regex("""BPM:\s*([\d.]+)""")
+  val spo2Regex = Regex("""SpO2:\s*(\d+)""")
+  val latRegex = Regex("""Latitude:\s*([\d.]+)""")
+  val lonRegex = Regex("""Longitude:\s*([\d.]+)""")
+  val bpm = bpmRegex.find(message)?.groupValues?.get(1) ?: "?"
+  val spo2 = spo2Regex.find(message)?.groupValues?.get(1) ?: "?"
+  val latStr = latRegex.find(message)?.groupValues?.get(1) ?: ""
+  val lonStr = lonRegex.find(message)?.groupValues?.get(1) ?: ""
+  pulseText.text = getString(R.string.bpm_format, bpm)
+  spo2Text.text = getString(R.string.spo2_format, spo2)
+  if (latStr.isNotEmpty() && lonStr.isNotEmpty()) {
+    gpsText.text = getString(R.string.location_format, latStr, lonStr)
+    lastLat = latStr
+    lastLon = lonStr
+    val lat = latStr.toDoubleOrNull()
+    val lon = lonStr.toDoubleOrNull()
+    val now = System.currentTimeMillis()
+    if (lat != null && lon != null) {
+      if (lastLatValue != null && lastLonValue != null && lastTimestamp != null) {
+        val speed = calculateSpeedKmH(
+          lastLatValue!!, lastLonValue!!, lastTimestamp!!,
+          lat, lon, now
+        )
+        speedText.text = getString(R.string.speed_format, "%.2f".format(speed))
+      }
+      lastLatValue = lat
+      lastLonValue = lon
+      lastTimestamp = now
+    }
+  }
+}
+</code>
+To estimate speed, the app implements a Haversine-based function, calculateSpeedKmH(), which computes the distance between two sets of latitude/longitude coordinates and divides it by the time difference. This allows the app to display an approximate speed in kilometers per hour (km/h), updated every time a new valid GPS coordinate is received.
+<code>
+private fun calculateSpeedKmH(
+  lat1: Double, lon1: Double, time1: Long,
+  lat2: Double, lon2: Double, time2: Long
+): Double {
+  val deltaTimeSec = (time2 - time1) / 1000.0
+  if (deltaTimeSec == 0.0) return 0.0
+  val R = 6371.0
+  val dLat = Math.toRadians(lat2 - lat1)
+  val dLon = Math.toRadians(lon2 - lon1)
+  val a = sin(dLat / 2).pow(2.0) +
+      cos(Math.toRadians(lat1)) * cos(Math.toRadians(lat2)) *
+      sin(dLon / 2).pow(2.0)
+  val c = 2 * atan2(sqrt(a), sqrt(1 - a))
+  val distanceKm = R * c
+  return distanceKm / (deltaTimeSec / 3600.0)
+}
+</code>
+==== Demonstration and Results ====
+To illustrate the functionality of the system, the images and logs offer a glimpse into how the components interact in practice, with real-time data flowing from the hardware to the mobile app.
+The Android application displays real-time values such as heart rate, oxygen saturation, speed, and GPS location in a clean interface.
+{{:iothings:proiecte:2025sric:app.jpg?300|}}
+Serial logs from the Arduino console show how data is continuously read from the GPS and pulse oximeter sensors.
+{{:iothings:proiecte:2025sric:monitor.png?570|}}
+the image shows the MAX30100 sensor in use for pulse measurement, alongside the GPS module actively providing location and speed data.
+{{:iothings:proiecte:2025sric:testspeed.jpg?570|}}
 ==== References ====
+  * [[https://randomnerdtutorials.com/esp32-neo-6m-gps-module-arduino/|ESP32 with NEO-6M GPS Module (Arduino IDE)]]
+  * [[https://www.electronicwings.com/esp32/max30100-pulse-oximeter-interfacing-with-esp32|MAX30100 Pulse Oximeter Interfacing with ESP32]]
+  * [[https://www.ridgesolutions.ie/index.php/2013/11/14/algorithm-to-calculate-speed-from-two-gps-latitude-and-longitude-points-and-time-difference/|Algorithm to calculate speed from two GPS latitude and longitude points and time difference]]