diff --git a/examples/fm_scanner.py b/examples/fm_scanner.py
new file mode 100755
index 0000000..9600dff
--- /dev/null
+++ b/examples/fm_scanner.py
@@ -0,0 +1,266 @@
+#!/usr/bin/env python3
+"""FM Band Scanner — scan 87.5–108.0 MHz using rtl_power, rank stations by signal strength."""
+
+import argparse
+import csv
+import io
+import json
+import shutil
+import subprocess
+import sys
+from collections import defaultdict
+from pathlib import Path
+
+
+def run_rtl_power(gain: int = 10) -> str:
+    """Execute rtl_power for a single FM band sweep and return raw CSV output.
+
+    The scan covers 87.5–108.0 MHz in 200 kHz bins (US FM channel spacing)
+    with 1-second integration time per sweep segment.
+    """
+    cmd = [
+        "rtl_power",
+        "-f", "87.5M:108M:200k",
+        "-g", str(gain),
+        "-i", "1",
+        "-1",  # single-shot
+        "-",   # stdout
+    ]
+    try:
+        result = subprocess.run(cmd, capture_output=True, text=True, timeout=30)
+    except FileNotFoundError:
+        print("Error: rtl_power not found. Install rtl-sdr tools.", file=sys.stderr)
+        sys.exit(1)
+    except subprocess.TimeoutExpired:
+        print("Error: rtl_power timed out after 30 seconds.", file=sys.stderr)
+        sys.exit(1)
+
+    if result.returncode != 0:
+        stderr = result.stderr.strip()
+        print(f"Error: rtl_power exited with code {result.returncode}", file=sys.stderr)
+        if stderr:
+            print(stderr, file=sys.stderr)
+        sys.exit(1)
+
+    return result.stdout
+
+
+def parse_scan(csv_data: str) -> list[tuple[float, float]]:
+    """Parse rtl_power CSV output into (frequency_mhz, power_dbm) pairs.
+
+    rtl_power CSV format per row:
+        date, time, freq_low_hz, freq_high_hz, bin_step_hz, num_samples, dBm, dBm, ...
+
+    Each row covers a frequency range with multiple FFT bins. We compute the
+    center frequency of each bin and pair it with its power reading.
+    """
+    readings: list[tuple[float, float]] = []
+
+    reader = csv.reader(io.StringIO(csv_data))
+    for row in reader:
+        if len(row) < 7:
+            continue
+        try:
+            freq_low = float(row[2].strip())
+            freq_high = float(row[3].strip())
+            bin_step = float(row[4].strip())
+            # num_samples = int(row[5].strip())  # not needed
+            power_values = [float(v.strip()) for v in row[6:] if v.strip()]
+        except (ValueError, IndexError):
+            continue
+
+        # Map each FFT bin to its center frequency
+        for i, power in enumerate(power_values):
+            freq_hz = freq_low + (i * bin_step) + (bin_step / 2)
+            freq_mhz = freq_hz / 1e6
+            readings.append((freq_mhz, power))
+
+    return readings
+
+
+def aggregate_channels(readings: list[tuple[float, float]]) -> list[dict]:
+    """Aggregate raw FFT bins into 200 kHz FM channels.
+
+    FM stations in the US are spaced at odd multiples of 100 kHz
+    (87.9, 88.1, 88.3, ..., 107.9). Each occupies ~200 kHz bandwidth.
+    We snap each reading to the nearest standard channel and take the
+    max power across all bins in that channel.
+    """
+    channel_bins: dict[float, list[float]] = defaultdict(list)
+
+    for freq_mhz, power in readings:
+        # Snap to nearest 0.2 MHz FM channel (87.5, 87.7, 87.9, ...)
+        channel = round(round(freq_mhz / 0.2) * 0.2, 1)
+        if 87.5 <= channel <= 108.0:
+            channel_bins[channel].append(power)
+
+    channels = []
+    for freq in sorted(channel_bins):
+        powers = channel_bins[freq]
+        # Use max power — peak represents the carrier
+        max_power = max(powers)
+        channels.append({"freq_mhz": freq, "power_dbm": max_power})
+
+    return channels
+
+
+def detect_stations(
+    channels: list[dict], threshold_db: float = 10.0
+) -> tuple[list[dict], float]:
+    """Find stations that rise above the noise floor.
+
+    The noise floor is estimated as the median power across all channels.
+    A channel is flagged as a station if its power exceeds
+    noise_floor + threshold_db.
+
+    Returns (stations_sorted_by_power, noise_floor_dbm).
+    """
+    if not channels:
+        return [], -99.0
+
+    powers = sorted(ch["power_dbm"] for ch in channels)
+    noise_floor = powers[len(powers) // 2]  # median
+
+    stations = []
+    for ch in channels:
+        snr = ch["power_dbm"] - noise_floor
+        if snr >= threshold_db:
+            stations.append({**ch, "snr_db": round(snr, 1)})
+
+    stations.sort(key=lambda s: s["power_dbm"], reverse=True)
+    return stations, noise_floor
+
+
+def display_results(
+    stations: list[dict],
+    noise_floor: float,
+    all_channels: list[dict] | None = None,
+    show_all: bool = False,
+):
+    """Print a formatted table of scan results to the terminal."""
+    term_width = shutil.get_terminal_size((80, 24)).columns
+    bar_max = max(32, term_width - 42)
+
+    items = all_channels if (show_all and all_channels) else stations
+    if not items:
+        print("No stations detected.")
+        return
+
+    # Bar scaling: use noise floor as baseline so every station gets a visible bar
+    powers = [ch["power_dbm"] for ch in items]
+    p_min = noise_floor
+    p_max = max(powers)
+    p_range = p_max - p_min if p_max != p_min else 1.0
+
+    header = "FM Band Scan \u2014 87.5 to 108.0 MHz"
+    print()
+    print(f"  {header}")
+    print(f"  {'═' * (len(header) + 2)}")
+    print(f"   {'#':>3}  {'Frequency':<12} {'Power':<10} Signal")
+    print(f"  {'─' * 3}  {'─' * 12} {'─' * 9} {'─' * bar_max}")
+
+    block_chars = " \u2581\u2582\u2583\u2584\u2585\u2586\u2587\u2588"
+
+    for i, ch in enumerate(items, 1):
+        freq = ch["freq_mhz"]
+        power = ch["power_dbm"]
+        # Normalize to [0, 1]
+        norm = max(0.0, min(1.0, (power - p_min) / p_range))
+        bar_len = norm * bar_max
+        full_blocks = int(bar_len)
+        frac = bar_len - full_blocks
+        frac_char = block_chars[int(frac * 8)] if frac > 0.05 else ""
+        bar = "\u2588" * full_blocks + frac_char
+
+        # Color: green for strong, yellow for mid, dim for weak
+        if "snr_db" in ch and ch["snr_db"] >= 10:
+            bar = f"\033[32m{bar}\033[0m"  # green
+        elif "snr_db" in ch:
+            bar = f"\033[33m{bar}\033[0m"  # yellow
+        elif show_all:
+            bar = f"\033[2m{bar}\033[0m"   # dim
+
+        label = f"{freq:>5.1f} MHz"
+        print(f"  {i:>3}  {label:<12} {power:>7.1f} dBm {bar}")
+
+    print(f"  {'═' * (len(header) + 2)}")
+    print(
+        f"  Noise floor: {noise_floor:.1f} dBm | "
+        f"Stations found: {len(stations)}"
+    )
+    print()
+
+
+def save_json(stations: list[dict], noise_floor: float, path: str):
+    """Write scan results to a JSON file."""
+    data = {
+        "band": "FM",
+        "range_mhz": [87.5, 108.0],
+        "noise_floor_dbm": round(noise_floor, 1),
+        "station_count": len(stations),
+        "stations": [
+            {
+                "freq_mhz": s["freq_mhz"],
+                "power_dbm": round(s["power_dbm"], 1),
+                "snr_db": s["snr_db"],
+            }
+            for s in stations
+        ],
+    }
+    Path(path).write_text(json.dumps(data, indent=2) + "\n")
+    print(f"Results saved to {path}")
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Scan the US FM band and rank stations by signal strength."
+    )
+    parser.add_argument(
+        "--threshold",
+        type=float,
+        default=10.0,
+        help="Minimum dB above noise floor to flag as station (default: 10)",
+    )
+    parser.add_argument(
+        "--gain",
+        type=int,
+        default=10,
+        help="RF tuner gain in dB (default: 10)",
+    )
+    parser.add_argument(
+        "--json",
+        metavar="FILE",
+        help="Save results to JSON file",
+    )
+    parser.add_argument(
+        "--all",
+        action="store_true",
+        dest="show_all",
+        help="Show all channels, not just detected stations",
+    )
+    args = parser.parse_args()
+
+    print("Scanning FM band (87.5–108.0 MHz)...", flush=True)
+    raw = run_rtl_power(gain=args.gain)
+
+    readings = parse_scan(raw)
+    if not readings:
+        print("No data received from rtl_power.", file=sys.stderr)
+        sys.exit(1)
+
+    channels = aggregate_channels(readings)
+    stations, noise_floor = detect_stations(channels, threshold_db=args.threshold)
+
+    display_results(
+        stations,
+        noise_floor,
+        all_channels=channels,
+        show_all=args.show_all,
+    )
+
+    if args.json:
+        save_json(stations, noise_floor, args.json)
+
+
+if __name__ == "__main__":
+    main()