Deploying IP cameras for a home lab, client project, or computer vision pipeline always hits the same wall: How much hard drive space do I actually need? Guessing wrong means either running out of NVR storage in three days or overspending on enterprise drives you don't need. On top of that, uncalculated video bitrates can easily choke your local network bandwidth.Here is the math behind calculating camera storage, how codecs affect file size, a quick Python script to estimate drive requirements, and a handy shortcut tool. The Core Math Behind CCTV Storage. Camera storage depends on five key variables: Bitrate (Mbps): How much data the camera streams per second.Number of Cameras: Total streams being recorded.Recording Hours per Day: 24/7 continuous vs. motion-triggered.Retention Period: Number of days to store footage before overwriting.Compression Codec: H.264, H.265, or vendor-specific "smart" codecs (H.265+).The Math FormulaTo calculate total required storage in Gigabytes (GB):$$\text{Storage (GB)} = \frac{\text{Bitrate (Mbps)} \times 3600 \text{ sec/hr} \times \text{Hours/Day} \times \text{Days} \times \text{Cameras}}{8 \times 1024}$$(Dividing by 8 converts Megabits to Megabytes, and dividing by 1024 converts Megabytes to Gigabytes).Average Bitrate Guidelines by ResolutionIf you don't know your camera's exact stream bitrate, here are standard averages for H.264 vs. H.265 codecs running at 15–20
FPS: Resolution Quality H.264 Bitrate H.265 Bitrate (50% Savings)1080p (2MP)Medium/High~4 Mbps~2 Mbps4MP (2K)Medium/High~6 Mbps~3 Mbps8MP (4K)Medium/High~12 Mbps~6 MbpsPython Storage Estimator ScriptYou can automate this calculation directly in Python to quickly evaluate different deployment scenarios:Python
`def calculate_cctv_storage(num_cameras: int, bitrate_mbps: float, days: int, hours_per_day: float = 24.0) -> dict:
# Calculate total megabits per day
seconds_per_day = hours_per_day * 3600
total_bits_per_day = bitrate_mbps * seconds_per_day * num_cameras * days

# Convert bits to Bytes (divide by 8), then to MB, GB, and TB

total_gb = total_bits_per_day / (8 * 1024)

total_tb = total_gb / 1024

  
  
  Calculate required bandwidth in Mbps


total_bandwidth_mbps = bitrate_mbps * num_cameras

return {

    "required_storage_gb": round(total_gb, 2),

    "required_storage_tb": round(total_tb, 2),

    "total_bandwidth_mbps": round(total_bandwidth_mbps, 2)

}

Example: 4 Cameras at 4MP (3 Mbps each on H.265) for 30 Days continuous recording

result = calculate_cctv_storage(num_cameras=4, bitrate_mbps=3.0, days=30)
print(f"Required HDD Space: {result['required_storage_tb']} TB")
print(f"Network Bandwidth: {result['total_bandwidth_mbps']} Mbps")

Output:

Required HDD Space: 3.71 TB

Network Bandwidth: 12.0 Mbps`

Quick Shortcut: Online CalculatorIf you want to quickly test multiple camera brands, variable frame rates, and different codec compression levels without recalculating manually, use an online CCTV storage calculator. It gives immediate HDD capacity estimates based on specific frame rates, resolutions, and retention schedules.3 Rules of Thumb for Storage Optimization: Cap FPS at 15: Unless you're monitoring a casino or highway traffic, 15 FPS provides smooth footage while cutting bitrate by nearly 50% compared to 30 FPS.Switch to H.265 / Smart Codecs: Switching from H.264 to H.265 immediately cuts bandwidth and storage overhead in half with zero loss in resolution.Use Motion-Triggered Recording for Secondary Zones: Hallways and back alleys don't need 24/7 continuous recording. Setting them to record on motion reduces storage requirements by up to 70%.