media-expert

Media Expert

Expert guidance for media production, content management systems, video streaming, broadcasting systems, and modern media technology solutions.

Core Concepts

Media Production

• Video production workflows
• Audio production and mixing
• Post-production and editing
• Visual effects (VFX)
• Color grading and correction
• Animation and motion graphics
• Live production

Streaming and Broadcasting

• Video streaming platforms
• Content Delivery Networks (CDN)
• Adaptive bitrate streaming
• Live broadcasting
• OTT (Over-the-Top) platforms
• Digital rights management (DRM)
• Transcoding and encoding

Technologies

• Media Asset Management (MAM)
• Digital Asset Management (DAM)
• Broadcast automation
• IP-based media production
• Cloud production workflows
• AI for content analysis
• Virtual production

Standards and Protocols

• SMPTE standards
• HLS (HTTP Live Streaming)
• DASH (Dynamic Adaptive Streaming over HTTP)
• RTMP/RTSP protocols
• NDI (Network Device Interface)
• MXF (Material Exchange Format)
• Metadata standards (Dublin Core, IPTC)

Video Streaming Platform

class VideoStreamingPlatform:
    """Video streaming and delivery system"""

    def __init__(self):
        self.streams = {}
        self.viewers = {}
        self.cdn_nodes = {}

    def start_live_stream(self, stream_data: dict) -> dict:
        """Start live video stream"""
        stream_id = self._generate_stream_id()

        stream = {
            'stream_id': stream_id,
            'title': stream_data['title'],
            'description': stream_data.get('description', ''),
            'streamer_id': stream_data['streamer_id'],
            'status': 'live',
            'started_at': datetime.now(),
            'viewer_count': 0,
            'peak_viewers': 0,
            'ingest_url': f'rtmp://ingest.example.com/live/{stream_id}',
            'playback_urls': {
                'hls': f'https://cdn.example.com/live/{stream_id}/playlist.m3u8',
                'dash': f'https://cdn.example.com/live/{stream_id}/manifest.mpd'
            },
            'quality_profiles': ['1080p', '720p', '480p', '360p']
        }

        self.streams[stream_id] = stream

        return stream

    def generate_adaptive_bitrate_manifest(self, asset_id: str) -> dict:
        """Generate ABR manifest for adaptive streaming"""
        # Generate HLS manifest
        hls_variants = [
            {
                'bandwidth': 5000000,  # 5 Mbps
                'resolution': '1920x1080',
                'codecs': 'avc1.640028,mp4a.40.2',
                'url': f'1080p/playlist.m3u8'
            },
            {
                'bandwidth': 2800000,  # 2.8 Mbps
                'resolution': '1280x720',
                'codecs': 'avc1.64001f,mp4a.40.2',
                'url': f'720p/playlist.m3u8'
            },
            {
                'bandwidth': 1400000,  # 1.4 Mbps
                'resolution': '854x480',
                'codecs': 'avc1.64001e,mp4a.40.2',
                'url': f'480p/playlist.m3u8'
            },
            {
                'bandwidth': 800000,  # 800 Kbps
                'resolution': '640x360',
                'codecs': 'avc1.64001e,mp4a.40.2',
                'url': f'360p/playlist.m3u8'
            }
        ]

        return {
            'asset_id': asset_id,
            'protocol': 'hls',
            'master_playlist_url': f'https://cdn.example.com/vod/{asset_id}/master.m3u8',
            'variants': hls_variants
        }

    def track_viewer_metrics(self, stream_id: str, viewer_id: str) -> dict:
        """Track viewer engagement metrics"""
        metrics = {
            'stream_id': stream_id,
            'viewer_id': viewer_id,
            'watch_time_seconds': 3600,
            'buffer_events': 2,
            'average_bitrate': 3500000,
            'quality_switches': 5,
            'playback_start_time_ms': 1200,
            'errors': 0,
            'device_type': 'desktop',
            'browser': 'chrome'
        }

        # Calculate Quality of Experience (QoE)
        qoe_score = self._calculate_qoe(metrics)
        metrics['qoe_score'] = qoe_score

        return metrics

    def _calculate_qoe(self, metrics: dict) -> float:
        """Calculate Quality of Experience score"""
        score = 100.0

        # Penalize buffering
        score -= metrics['buffer_events'] * 5

        # Penalize startup time
        if metrics['playback_start_time_ms'] > 2000:
            score -= 10

        # Penalize errors
        score -= metrics['errors'] * 15

        return max(0.0, score)

    def implement_drm(self, asset_id: str, drm_config: dict) -> dict:
        """Implement Digital Rights Management"""
        drm = {
            'asset_id': asset_id,
            'drm_systems': {
                'widevine': {
                    'license_url': 'https://license.example.com/widevine',
                    'supported_levels': ['L1', 'L3']
                },
                'fairplay': {
                    'certificate_url': 'https://license.example.com/fairplay/cert',
                    'license_url': 'https://license.example.com/fairplay/license'
                },
                'playready': {
                    'license_url': 'https://license.example.com/playready'
                }
            },
            'encryption': 'AES-128-CTR',
            'key_rotation_interval': 3600  # seconds
        }

        return drm

    def optimize_cdn_delivery(self, asset_id: str, viewer_location: tuple) -> dict:
        """Optimize CDN delivery based on viewer location"""
        # Find nearest CDN edge node
        nearest_node = self._find_nearest_cdn_node(viewer_location)

        return {
            'asset_id': asset_id,
            'cdn_node': nearest_node['node_id'],
            'cdn_location': nearest_node['location'],
            'distance_km': nearest_node['distance'],
            'estimated_latency_ms': nearest_node['latency'],
            'delivery_url': f"https://{nearest_node['node_id']}.cdn.example.com/{asset_id}"
        }

    def _find_nearest_cdn_node(self, viewer_location: tuple) -> dict:
        """Find nearest CDN edge node to viewer"""
        # Would calculate actual distances to CDN nodes
        return {
            'node_id': 'edge-us-east-1',
            'location': 'Virginia, USA',
            'distance': 250,  # km
            'latency': 15  # ms
        }

    def _generate_stream_id(self) -> str:
        import uuid
        return f"STREAM-{uuid.uuid4().hex[:8].upper()}"