Add room and analytics services with CRUD API endpoints
- Implement RoomService for room management and metrics - Add AnalyticsService for sensor data analytics and trends - Extend models with Room, RoomCreate, RoomUpdate, RoomInfo - Add room CRUD endpoints to FastAPI app - Add database connection logic for MongoDB and Redis - Refactor sensor service logic into SensorService class
This commit is contained in:
rafaeldpsilva
377
microservices/sensor-service/analytics_service.py
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377
microservices/sensor-service/analytics_service.py
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@@ -0,0 +1,377 @@
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"""
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Analytics service for processing sensor data and generating insights
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"""
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import logging
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from datetime import datetime, timedelta
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from typing import List, Dict, Any, Optional
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import json
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logger = logging.getLogger(__name__)
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class AnalyticsService:
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"""Service for analytics and data processing"""
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def __init__(self, db, redis_client):
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self.db = db
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self.redis = redis_client
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async def query_data(self, query_params) -> Dict[str, Any]:
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"""Execute advanced data query"""
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try:
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# Build query
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query = {}
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if hasattr(query_params, 'sensor_ids') and query_params.sensor_ids:
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query["sensor_id"] = {"$in": query_params.sensor_ids}
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if hasattr(query_params, 'start_time') and query_params.start_time:
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query.setdefault("timestamp", {})["$gte"] = query_params.start_time
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if hasattr(query_params, 'end_time') and query_params.end_time:
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query.setdefault("timestamp", {})["$lte"] = query_params.end_time
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# Execute query
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cursor = self.db.sensor_readings.find(query)
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if hasattr(query_params, 'limit') and query_params.limit:
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cursor = cursor.limit(query_params.limit)
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if hasattr(query_params, 'offset') and query_params.offset:
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cursor = cursor.skip(query_params.offset)
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cursor = cursor.sort("timestamp", -1)
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# Get results
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results = []
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async for reading in cursor:
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reading["_id"] = str(reading["_id"])
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results.append(reading)
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# Get total count
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total_count = await self.db.sensor_readings.count_documents(query)
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return {
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"data": results,
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"total_count": total_count,
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"query": query_params.__dict__ if hasattr(query_params, '__dict__') else {},
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"execution_time_ms": 0 # Placeholder
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}
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except Exception as e:
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logger.error(f"Error executing data query: {e}")
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raise
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async def get_analytics_summary(self, hours: int = 24) -> Dict[str, Any]:
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"""Get comprehensive analytics summary"""
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try:
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start_time = datetime.utcnow() - timedelta(hours=hours)
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# Get basic statistics
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pipeline = [
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{
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"$match": {
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"created_at": {"$gte": start_time}
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}
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},
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{
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"$group": {
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"_id": None,
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"total_readings": {"$sum": 1},
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"average_value": {"$avg": "$value"},
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"min_value": {"$min": "$value"},
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"max_value": {"$max": "$value"},
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"unique_sensors": {"$addToSet": "$sensor_id"}
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}
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}
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]
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cursor = self.db.sensor_readings.aggregate(pipeline)
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stats = await cursor.to_list(length=1)
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base_stats = stats[0] if stats else {
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"total_readings": 0,
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"average_value": 0,
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"min_value": 0,
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"max_value": 0,
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"unique_sensors": []
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}
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# Get room-level statistics
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room_stats = await self._get_room_analytics(hours)
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# Get energy trends
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energy_trends = await self._get_energy_trends(hours)
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return {
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"period_hours": hours,
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"timestamp": datetime.utcnow().isoformat(),
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"total_readings": base_stats["total_readings"],
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"unique_sensors": len(base_stats["unique_sensors"]),
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"value_statistics": {
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"average": round(base_stats["average_value"], 2) if base_stats["average_value"] else 0,
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"minimum": base_stats["min_value"],
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"maximum": base_stats["max_value"]
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},
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"room_statistics": room_stats,
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"energy_trends": energy_trends
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}
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except Exception as e:
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logger.error(f"Error getting analytics summary: {e}")
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raise
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async def get_energy_analytics(self, hours: int = 24, room: Optional[str] = None) -> Dict[str, Any]:
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"""Get energy-specific analytics"""
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try:
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start_time = datetime.utcnow() - timedelta(hours=hours)
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# Build query
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query = {"created_at": {"$gte": start_time}}
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if room:
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query["room"] = room
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# Energy consumption over time
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pipeline = [
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{"$match": query},
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{
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"$group": {
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"_id": {
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"hour": {"$hour": "$created_at"},
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"date": {"$dateToString": {"format": "%Y-%m-%d", "date": "$created_at"}}
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},
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"total_energy": {"$sum": "$value"},
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"reading_count": {"$sum": 1}
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}
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},
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{"$sort": {"_id.date": 1, "_id.hour": 1}}
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]
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cursor = self.db.sensor_readings.aggregate(pipeline)
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hourly_data = []
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async for data in cursor:
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hourly_data.append({
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"hour": data["_id"]["hour"],
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"date": data["_id"]["date"],
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"total_energy": data["total_energy"],
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"reading_count": data["reading_count"]
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})
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# Peak consumption analysis
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peak_analysis = await self._get_peak_consumption_analysis(query)
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# Energy efficiency metrics
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efficiency_metrics = await self._get_efficiency_metrics(query)
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return {
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"period_hours": hours,
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"room": room,
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"timestamp": datetime.utcnow().isoformat(),
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"hourly_consumption": hourly_data,
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"peak_analysis": peak_analysis,
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"efficiency_metrics": efficiency_metrics,
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"total_consumption": sum(item["total_energy"] for item in hourly_data)
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}
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except Exception as e:
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logger.error(f"Error getting energy analytics: {e}")
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raise
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async def _get_room_analytics(self, hours: int) -> Dict[str, Any]:
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"""Get room-level analytics"""
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try:
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start_time = datetime.utcnow() - timedelta(hours=hours)
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pipeline = [
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{
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"$match": {
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"created_at": {"$gte": start_time},
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"room": {"$ne": None}
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}
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},
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{
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"$group": {
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"_id": "$room",
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"total_readings": {"$sum": 1},
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"total_energy": {"$sum": "$value"},
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"average_energy": {"$avg": "$value"},
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"unique_sensors": {"$addToSet": "$sensor_id"}
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}
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},
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{"$sort": {"total_energy": -1}}
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]
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cursor = self.db.sensor_readings.aggregate(pipeline)
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room_data = []
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async for room in cursor:
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room_data.append({
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"room": room["_id"],
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"total_readings": room["total_readings"],
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"total_energy": room["total_energy"],
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"average_energy": round(room["average_energy"], 2),
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"sensor_count": len(room["unique_sensors"])
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})
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return {
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"by_room": room_data,
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"total_rooms": len(room_data)
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}
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except Exception as e:
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logger.error(f"Error getting room analytics: {e}")
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return {"by_room": [], "total_rooms": 0}
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async def _get_energy_trends(self, hours: int) -> Dict[str, Any]:
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"""Get energy consumption trends"""
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try:
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start_time = datetime.utcnow() - timedelta(hours=hours)
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# Get current period data
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current_query = {"created_at": {"$gte": start_time}}
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current_cursor = self.db.sensor_readings.aggregate([
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{"$match": current_query},
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{"$group": {"_id": None, "total": {"$sum": "$value"}, "count": {"$sum": 1}}}
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])
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current_data = await current_cursor.to_list(length=1)
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current_total = current_data[0]["total"] if current_data else 0
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current_count = current_data[0]["count"] if current_data else 0
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# Get previous period for comparison
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previous_start = start_time - timedelta(hours=hours)
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previous_query = {
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"created_at": {"$gte": previous_start, "$lt": start_time}
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}
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previous_cursor = self.db.sensor_readings.aggregate([
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{"$match": previous_query},
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{"$group": {"_id": None, "total": {"$sum": "$value"}, "count": {"$sum": 1}}}
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])
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previous_data = await previous_cursor.to_list(length=1)
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previous_total = previous_data[0]["total"] if previous_data else 0
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# Calculate trend
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if previous_total > 0:
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trend_percentage = ((current_total - previous_total) / previous_total) * 100
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else:
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trend_percentage = 0
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return {
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"current_period": {
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"total_energy": current_total,
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"reading_count": current_count,
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"average_per_reading": current_total / current_count if current_count > 0 else 0
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},
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"previous_period": {
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"total_energy": previous_total
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},
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"trend": {
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"percentage_change": round(trend_percentage, 2),
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"direction": "up" if trend_percentage > 0 else "down" if trend_percentage < 0 else "stable"
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}
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}
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except Exception as e:
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logger.error(f"Error getting energy trends: {e}")
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return {}
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async def _get_peak_consumption_analysis(self, base_query: Dict[str, Any]) -> Dict[str, Any]:
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"""Analyze peak consumption patterns"""
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try:
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pipeline = [
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{"$match": base_query},
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{
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"$group": {
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"_id": {"$hour": "$created_at"},
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"total_consumption": {"$sum": "$value"},
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"reading_count": {"$sum": 1}
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}
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},
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{"$sort": {"total_consumption": -1}}
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]
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cursor = self.db.sensor_readings.aggregate(pipeline)
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hourly_consumption = await cursor.to_list(length=None)
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if not hourly_consumption:
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return {"peak_hour": None, "peak_consumption": 0, "hourly_pattern": []}
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peak_data = hourly_consumption[0]
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return {
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"peak_hour": peak_data["_id"],
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"peak_consumption": peak_data["total_consumption"],
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"hourly_pattern": [
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{
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"hour": item["_id"],
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"consumption": item["total_consumption"],
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"reading_count": item["reading_count"]
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}
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for item in hourly_consumption
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]
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}
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except Exception as e:
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logger.error(f"Error analyzing peak consumption: {e}")
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return {"peak_hour": None, "peak_consumption": 0, "hourly_pattern": []}
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async def _get_efficiency_metrics(self, base_query: Dict[str, Any]) -> Dict[str, Any]:
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"""Calculate energy efficiency metrics"""
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try:
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# Average consumption per sensor
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pipeline = [
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{"$match": base_query},
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{
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"$group": {
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"_id": "$sensor_id",
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"total_consumption": {"$sum": "$value"},
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"reading_count": {"$sum": 1}
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}
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},
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{
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"$group": {
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"_id": None,
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"average_per_sensor": {"$avg": "$total_consumption"},
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"sensor_count": {"$sum": 1},
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"min_consumption": {"$min": "$total_consumption"},
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"max_consumption": {"$max": "$total_consumption"}
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}
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}
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]
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cursor = self.db.sensor_readings.aggregate(pipeline)
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efficiency_data = await cursor.to_list(length=1)
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if not efficiency_data:
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return {
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"average_per_sensor": 0,
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"sensor_count": 0,
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"efficiency_score": 0,
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"variation_coefficient": 0
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}
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data = efficiency_data[0]
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# Calculate efficiency score (lower variation = higher efficiency)
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if data["average_per_sensor"] > 0:
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variation_coefficient = (data["max_consumption"] - data["min_consumption"]) / data["average_per_sensor"]
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efficiency_score = max(0, 100 - (variation_coefficient * 10)) # Scale to 0-100
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else:
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variation_coefficient = 0
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efficiency_score = 100
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return {
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"average_per_sensor": round(data["average_per_sensor"], 2),
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"sensor_count": data["sensor_count"],
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"efficiency_score": round(efficiency_score, 1),
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"variation_coefficient": round(variation_coefficient, 2)
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}
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except Exception as e:
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logger.error(f"Error calculating efficiency metrics: {e}")
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return {
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"average_per_sensor": 0,
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"sensor_count": 0,
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"efficiency_score": 0,
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"variation_coefficient": 0
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}
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66
microservices/sensor-service/database.py
Normal file
66
microservices/sensor-service/database.py
Normal file
@@ -0,0 +1,66 @@
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"""
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Database connection and management for sensor service
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"""
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import asyncio
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import logging
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from motor.motor_asyncio import AsyncIOMotorClient
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import redis.asyncio as redis
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from typing import Optional
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import os
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logger = logging.getLogger(__name__)
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# Global database connections
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mongo_client: Optional[AsyncIOMotorClient] = None
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redis_client: Optional[redis.Redis] = None
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database = None
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async def connect_to_mongo():
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"""Connect to MongoDB"""
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global mongo_client, database
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try:
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mongo_url = os.getenv("MONGO_URL", "mongodb://admin:password123@mongodb:27017/energy_dashboard_sensors?authSource=admin")
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mongo_client = AsyncIOMotorClient(mongo_url)
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database = mongo_client.energy_dashboard_sensors
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# Test connection
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await mongo_client.admin.command('ping')
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logger.info("Connected to MongoDB successfully")
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except Exception as e:
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logger.error(f"Failed to connect to MongoDB: {e}")
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raise
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async def close_mongo_connection():
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"""Close MongoDB connection"""
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global mongo_client
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if mongo_client:
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mongo_client.close()
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logger.info("Closed MongoDB connection")
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async def connect_to_redis():
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"""Connect to Redis"""
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global redis_client
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try:
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redis_url = os.getenv("REDIS_URL", "redis://redis:6379")
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redis_client = redis.from_url(redis_url, decode_responses=True)
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# Test connection
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await redis_client.ping()
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logger.info("Connected to Redis successfully")
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except Exception as e:
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logger.error(f"Failed to connect to Redis: {e}")
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raise
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async def get_database():
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"""Get database instance"""
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return database
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async def get_redis():
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"""Get Redis client instance"""
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return redis_client
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@@ -16,7 +16,8 @@ import json
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from models import (
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SensorReading, SensorMetadata, RoomMetrics, SystemEvent, DataQuery, DataResponse,
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SensorType, SensorStatus, CO2Status, OccupancyLevel, HealthResponse
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SensorType, SensorStatus, CO2Status, OccupancyLevel, HealthResponse,
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Room, RoomCreate, RoomUpdate, RoomInfo
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)
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from database import connect_to_mongo, close_mongo_connection, get_database, connect_to_redis, get_redis
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from sensor_service import SensorService
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@@ -38,6 +39,12 @@ async def lifespan(app: FastAPI):
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await connect_to_mongo()
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await connect_to_redis()
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# Initialize default rooms if none exist
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db = await get_database()
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redis_client = await get_redis()
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room_service = RoomService(db, redis_client)
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await room_service.initialize_default_rooms()
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# Start background tasks
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asyncio.create_task(redis_subscriber_task())
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asyncio.create_task(room_metrics_aggregation_task())
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@@ -250,6 +257,19 @@ async def delete_sensor(
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raise HTTPException(status_code=500, detail="Internal server error")
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# Room Management
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@app.get("/rooms/names")
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async def get_room_names(service: RoomService = Depends(get_room_service)):
|
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"""Get simple list of room names for dropdowns"""
|
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try:
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room_names = await service.get_all_room_names()
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return {
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"rooms": room_names,
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"count": len(room_names)
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}
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||||
except Exception as e:
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||||
logger.error(f"Error getting room names: {e}")
|
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raise HTTPException(status_code=500, detail="Internal server error")
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||||
|
||||
@app.get("/rooms")
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async def get_rooms(service: RoomService = Depends(get_room_service)):
|
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"""Get all rooms with sensor counts and metrics"""
|
||||
@@ -265,16 +285,16 @@ async def get_rooms(service: RoomService = Depends(get_room_service)):
|
||||
|
||||
@app.post("/rooms")
|
||||
async def create_room(
|
||||
room_data: dict,
|
||||
room_data: RoomCreate,
|
||||
service: RoomService = Depends(get_room_service)
|
||||
):
|
||||
"""Create a new room"""
|
||||
try:
|
||||
result = await service.create_room(room_data)
|
||||
result = await service.create_room(room_data.dict())
|
||||
return {
|
||||
"message": "Room created successfully",
|
||||
"room": room_data.get("name"),
|
||||
"created_at": result.get("created_at")
|
||||
"room": result["name"],
|
||||
"created_at": result["created_at"]
|
||||
}
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
@@ -282,6 +302,40 @@ async def create_room(
|
||||
logger.error(f"Error creating room: {e}")
|
||||
raise HTTPException(status_code=500, detail="Internal server error")
|
||||
|
||||
@app.put("/rooms/{room_name}")
|
||||
async def update_room(
|
||||
room_name: str,
|
||||
room_data: RoomUpdate,
|
||||
service: RoomService = Depends(get_room_service)
|
||||
):
|
||||
"""Update an existing room"""
|
||||
try:
|
||||
result = await service.update_room(room_name, room_data.dict(exclude_unset=True))
|
||||
return {
|
||||
"message": "Room updated successfully",
|
||||
"room": result["name"],
|
||||
"updated_at": result["updated_at"],
|
||||
"modified": result["modified"]
|
||||
}
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=404, detail=str(e))
|
||||
except Exception as e:
|
||||
logger.error(f"Error updating room {room_name}: {e}")
|
||||
raise HTTPException(status_code=500, detail="Internal server error")
|
||||
|
||||
@app.delete("/rooms/{room_name}")
|
||||
async def delete_room(room_name: str, service: RoomService = Depends(get_room_service)):
|
||||
"""Delete a room"""
|
||||
try:
|
||||
result = await service.delete_room(room_name)
|
||||
return {
|
||||
"message": "Room deleted successfully",
|
||||
**result
|
||||
}
|
||||
except Exception as e:
|
||||
logger.error(f"Error deleting room {room_name}: {e}")
|
||||
raise HTTPException(status_code=500, detail="Internal server error")
|
||||
|
||||
@app.get("/rooms/{room_name}")
|
||||
async def get_room(room_name: str, service: RoomService = Depends(get_room_service)):
|
||||
"""Get detailed room information"""
|
||||
|
||||
@@ -296,6 +296,69 @@ class AnalyticsSummary(BaseModel):
|
||||
datetime: lambda v: v.isoformat()
|
||||
}
|
||||
|
||||
# Room Management Models
|
||||
class Room(BaseModel):
|
||||
"""Room model for database storage and API responses"""
|
||||
name: str = Field(..., description="Unique room name")
|
||||
description: Optional[str] = Field(None, description="Room description")
|
||||
floor: Optional[str] = Field(None, description="Floor designation")
|
||||
building: Optional[str] = Field(None, description="Building name")
|
||||
area: Optional[float] = Field(None, description="Room area in square meters")
|
||||
capacity: Optional[int] = Field(None, description="Maximum occupancy")
|
||||
room_type: Optional[str] = Field(None, description="Room type (office, meeting, storage, etc.)")
|
||||
|
||||
# Metadata
|
||||
created_at: datetime = Field(default_factory=datetime.utcnow, description="Room creation timestamp")
|
||||
updated_at: datetime = Field(default_factory=datetime.utcnow, description="Room update timestamp")
|
||||
|
||||
class Config:
|
||||
json_encoders = {
|
||||
datetime: lambda v: v.isoformat() if v else None
|
||||
}
|
||||
|
||||
class RoomCreate(BaseModel):
|
||||
"""Model for creating new rooms"""
|
||||
name: str = Field(..., description="Unique room name", min_length=1, max_length=100)
|
||||
description: Optional[str] = Field(None, description="Room description", max_length=500)
|
||||
floor: Optional[str] = Field(None, description="Floor designation", max_length=50)
|
||||
building: Optional[str] = Field(None, description="Building name", max_length=100)
|
||||
area: Optional[float] = Field(None, description="Room area in square meters", gt=0)
|
||||
capacity: Optional[int] = Field(None, description="Maximum occupancy", gt=0)
|
||||
room_type: Optional[str] = Field(None, description="Room type", max_length=50)
|
||||
|
||||
class RoomUpdate(BaseModel):
|
||||
"""Model for updating existing rooms"""
|
||||
description: Optional[str] = Field(None, description="Room description", max_length=500)
|
||||
floor: Optional[str] = Field(None, description="Floor designation", max_length=50)
|
||||
building: Optional[str] = Field(None, description="Building name", max_length=100)
|
||||
area: Optional[float] = Field(None, description="Room area in square meters", gt=0)
|
||||
capacity: Optional[int] = Field(None, description="Maximum occupancy", gt=0)
|
||||
room_type: Optional[str] = Field(None, description="Room type", max_length=50)
|
||||
|
||||
class RoomInfo(BaseModel):
|
||||
"""Comprehensive room information for API responses"""
|
||||
name: str = Field(..., description="Room name")
|
||||
description: Optional[str] = Field(None, description="Room description")
|
||||
floor: Optional[str] = Field(None, description="Floor designation")
|
||||
building: Optional[str] = Field(None, description="Building name")
|
||||
area: Optional[float] = Field(None, description="Room area in square meters")
|
||||
capacity: Optional[int] = Field(None, description="Maximum occupancy")
|
||||
room_type: Optional[str] = Field(None, description="Room type")
|
||||
|
||||
# Runtime information
|
||||
sensor_count: int = Field(0, description="Number of sensors in room")
|
||||
active_sensors: int = Field(0, description="Number of active sensors")
|
||||
last_updated: Optional[datetime] = Field(None, description="Last metrics update")
|
||||
|
||||
# Timestamps
|
||||
created_at: datetime = Field(..., description="Room creation timestamp")
|
||||
updated_at: datetime = Field(..., description="Room update timestamp")
|
||||
|
||||
class Config:
|
||||
json_encoders = {
|
||||
datetime: lambda v: v.isoformat() if v else None
|
||||
}
|
||||
|
||||
class HealthResponse(BaseModel):
|
||||
"""Health check response"""
|
||||
service: str
|
||||
|
||||
467
microservices/sensor-service/room_service.py
Normal file
467
microservices/sensor-service/room_service.py
Normal file
@@ -0,0 +1,467 @@
|
||||
"""
|
||||
Room service for managing rooms and room-level metrics
|
||||
"""
|
||||
|
||||
import logging
|
||||
from datetime import datetime, timedelta
|
||||
from typing import List, Dict, Any, Optional
|
||||
import json
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class RoomService:
|
||||
"""Service for managing rooms and room-level analytics"""
|
||||
|
||||
def __init__(self, db, redis_client):
|
||||
self.db = db
|
||||
self.redis = redis_client
|
||||
|
||||
async def get_all_room_names(self) -> List[str]:
|
||||
"""Get a simple list of all room names for dropdowns/selections"""
|
||||
try:
|
||||
# Get rooms from the rooms collection
|
||||
room_cursor = self.db.rooms.find({}, {"name": 1})
|
||||
room_names = set()
|
||||
|
||||
async for room in room_cursor:
|
||||
room_names.add(room["name"])
|
||||
|
||||
# Also get rooms that exist only in sensor data (legacy support)
|
||||
sensor_cursor = self.db.sensors.find(
|
||||
{"room": {"$ne": None, "$exists": True}},
|
||||
{"room": 1}
|
||||
)
|
||||
|
||||
async for sensor in sensor_cursor:
|
||||
if sensor.get("room"):
|
||||
room_names.add(sensor["room"])
|
||||
|
||||
# Convert to sorted list
|
||||
return sorted(list(room_names))
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting room names: {e}")
|
||||
raise
|
||||
|
||||
async def initialize_default_rooms(self) -> None:
|
||||
"""Initialize default rooms if none exist"""
|
||||
try:
|
||||
# Check if any rooms exist
|
||||
room_count = await self.db.rooms.count_documents({})
|
||||
|
||||
if room_count == 0:
|
||||
# Create default rooms
|
||||
default_rooms = [
|
||||
{"name": "Conference Room A", "description": "Main conference room", "room_type": "meeting"},
|
||||
{"name": "Conference Room B", "description": "Secondary conference room", "room_type": "meeting"},
|
||||
{"name": "Office Floor 1", "description": "First floor office space", "room_type": "office"},
|
||||
{"name": "Office Floor 2", "description": "Second floor office space", "room_type": "office"},
|
||||
{"name": "Kitchen", "description": "Employee kitchen and break room", "room_type": "common"},
|
||||
{"name": "Lobby", "description": "Main entrance and reception", "room_type": "common"},
|
||||
{"name": "Server Room", "description": "IT equipment room", "room_type": "technical"},
|
||||
{"name": "Storage Room", "description": "General storage", "room_type": "storage"},
|
||||
{"name": "Meeting Room 1", "description": "Small meeting room", "room_type": "meeting"},
|
||||
{"name": "Meeting Room 2", "description": "Small meeting room", "room_type": "meeting"}
|
||||
]
|
||||
|
||||
for room_data in default_rooms:
|
||||
room_doc = {
|
||||
**room_data,
|
||||
"created_at": datetime.utcnow(),
|
||||
"updated_at": datetime.utcnow()
|
||||
}
|
||||
await self.db.rooms.insert_one(room_doc)
|
||||
|
||||
logger.info(f"Initialized {len(default_rooms)} default rooms")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error initializing default rooms: {e}")
|
||||
raise
|
||||
|
||||
async def get_rooms(self) -> List[Dict[str, Any]]:
|
||||
"""Get all rooms with sensor counts and metrics"""
|
||||
try:
|
||||
# Get unique rooms from sensors
|
||||
pipeline = [
|
||||
{"$group": {"_id": "$room", "sensor_count": {"$sum": 1}}},
|
||||
{"$match": {"_id": {"$ne": None}}}
|
||||
]
|
||||
|
||||
cursor = self.db.sensors.aggregate(pipeline)
|
||||
rooms = []
|
||||
|
||||
async for room_data in cursor:
|
||||
room_name = room_data["_id"]
|
||||
|
||||
# Get latest room metrics
|
||||
latest_metrics = await self._get_latest_room_metrics(room_name)
|
||||
|
||||
room_info = {
|
||||
"name": room_name,
|
||||
"sensor_count": room_data["sensor_count"],
|
||||
"latest_metrics": latest_metrics,
|
||||
"last_updated": latest_metrics.get("timestamp") if latest_metrics else None
|
||||
}
|
||||
|
||||
rooms.append(room_info)
|
||||
|
||||
return rooms
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting rooms: {e}")
|
||||
raise
|
||||
|
||||
async def create_room(self, room_data: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""Create a new room"""
|
||||
try:
|
||||
room_doc = {
|
||||
"name": room_data.get("name"),
|
||||
"description": room_data.get("description", ""),
|
||||
"floor": room_data.get("floor"),
|
||||
"building": room_data.get("building"),
|
||||
"area": room_data.get("area"),
|
||||
"capacity": room_data.get("capacity"),
|
||||
"room_type": room_data.get("room_type"),
|
||||
"created_at": datetime.utcnow(),
|
||||
"updated_at": datetime.utcnow()
|
||||
}
|
||||
|
||||
# Validate required fields
|
||||
if not room_doc["name"] or not room_doc["name"].strip():
|
||||
raise ValueError("Room name is required")
|
||||
|
||||
# Check if room already exists
|
||||
existing = await self.db.rooms.find_one({"name": room_doc["name"]})
|
||||
if existing:
|
||||
raise ValueError(f"Room {room_doc['name']} already exists")
|
||||
|
||||
result = await self.db.rooms.insert_one(room_doc)
|
||||
|
||||
return {
|
||||
"id": str(result.inserted_id),
|
||||
"name": room_doc["name"],
|
||||
"created_at": room_doc["created_at"]
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error creating room: {e}")
|
||||
raise
|
||||
|
||||
async def update_room(self, room_name: str, room_data: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""Update an existing room"""
|
||||
try:
|
||||
# Check if room exists
|
||||
existing = await self.db.rooms.find_one({"name": room_name})
|
||||
if not existing:
|
||||
raise ValueError(f"Room {room_name} not found")
|
||||
|
||||
# Prepare update document
|
||||
update_doc = {
|
||||
"updated_at": datetime.utcnow()
|
||||
}
|
||||
|
||||
# Update only provided fields
|
||||
for field in ["description", "floor", "building", "area", "capacity", "room_type"]:
|
||||
if field in room_data and room_data[field] is not None:
|
||||
update_doc[field] = room_data[field]
|
||||
|
||||
# Perform update
|
||||
result = await self.db.rooms.update_one(
|
||||
{"name": room_name},
|
||||
{"$set": update_doc}
|
||||
)
|
||||
|
||||
if result.modified_count == 0:
|
||||
logger.warning(f"No changes made to room {room_name}")
|
||||
|
||||
return {
|
||||
"name": room_name,
|
||||
"updated_at": update_doc["updated_at"],
|
||||
"modified": result.modified_count > 0
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error updating room: {e}")
|
||||
raise
|
||||
|
||||
async def delete_room(self, room_name: str) -> Dict[str, Any]:
|
||||
"""Delete a room and optionally reassign sensors"""
|
||||
try:
|
||||
# Check if room exists
|
||||
existing = await self.db.rooms.find_one({"name": room_name})
|
||||
|
||||
# Check for sensors in this room
|
||||
sensors_in_room = await self.db.sensors.find({"room": room_name}).to_list(None)
|
||||
|
||||
if sensors_in_room:
|
||||
# Update sensors to have null room (don't delete sensors)
|
||||
await self.db.sensors.update_many(
|
||||
{"room": room_name},
|
||||
{"$unset": {"room": ""}}
|
||||
)
|
||||
|
||||
# Delete room from rooms collection if it exists
|
||||
room_deleted = False
|
||||
if existing:
|
||||
result = await self.db.rooms.delete_one({"name": room_name})
|
||||
room_deleted = result.deleted_count > 0
|
||||
|
||||
# Delete room metrics
|
||||
metrics_result = await self.db.room_metrics.delete_many({"room": room_name})
|
||||
|
||||
return {
|
||||
"room": room_name,
|
||||
"room_deleted": room_deleted,
|
||||
"sensors_updated": len(sensors_in_room),
|
||||
"metrics_deleted": metrics_result.deleted_count
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error deleting room: {e}")
|
||||
raise
|
||||
|
||||
async def get_room_details(self, room_name: str) -> Optional[Dict[str, Any]]:
|
||||
"""Get detailed room information"""
|
||||
try:
|
||||
# Get room info
|
||||
room = await self.db.rooms.find_one({"name": room_name})
|
||||
|
||||
if not room:
|
||||
# Create basic room info from sensor data
|
||||
sensors = await self.db.sensors.find({"room": room_name}).to_list(None)
|
||||
if not sensors:
|
||||
return None
|
||||
|
||||
room = {
|
||||
"name": room_name,
|
||||
"description": f"Room with {len(sensors)} sensors",
|
||||
"sensor_count": len(sensors)
|
||||
}
|
||||
else:
|
||||
room["_id"] = str(room["_id"])
|
||||
|
||||
# Get sensor count
|
||||
sensor_count = await self.db.sensors.count_documents({"room": room_name})
|
||||
room["sensor_count"] = sensor_count
|
||||
|
||||
# Get sensors in this room
|
||||
cursor = self.db.sensors.find({"room": room_name})
|
||||
sensors = []
|
||||
async for sensor in cursor:
|
||||
sensor["_id"] = str(sensor["_id"])
|
||||
sensors.append(sensor)
|
||||
|
||||
room["sensors"] = sensors
|
||||
|
||||
# Get recent room metrics
|
||||
room["recent_metrics"] = await self._get_recent_room_metrics(room_name, hours=24)
|
||||
|
||||
return room
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting room details: {e}")
|
||||
raise
|
||||
|
||||
async def get_room_data(self, room_name: str, start_time: Optional[int] = None,
|
||||
end_time: Optional[int] = None, limit: int = 100) -> Dict[str, Any]:
|
||||
"""Get historical data for a room"""
|
||||
try:
|
||||
# Get room metrics
|
||||
room_query = {"room": room_name}
|
||||
if start_time or end_time:
|
||||
room_query["timestamp"] = {}
|
||||
if start_time:
|
||||
room_query["timestamp"]["$gte"] = start_time
|
||||
if end_time:
|
||||
room_query["timestamp"]["$lte"] = end_time
|
||||
|
||||
room_metrics_cursor = self.db.room_metrics.find(room_query).sort("timestamp", -1).limit(limit)
|
||||
room_metrics = []
|
||||
async for metric in room_metrics_cursor:
|
||||
metric["_id"] = str(metric["_id"])
|
||||
room_metrics.append(metric)
|
||||
|
||||
# Get sensor readings for this room
|
||||
sensor_query = {"room": room_name}
|
||||
if start_time or end_time:
|
||||
sensor_query["timestamp"] = {}
|
||||
if start_time:
|
||||
sensor_query["timestamp"]["$gte"] = start_time
|
||||
if end_time:
|
||||
sensor_query["timestamp"]["$lte"] = end_time
|
||||
|
||||
sensor_readings_cursor = self.db.sensor_readings.find(sensor_query).sort("timestamp", -1).limit(limit)
|
||||
sensor_readings = []
|
||||
async for reading in sensor_readings_cursor:
|
||||
reading["_id"] = str(reading["_id"])
|
||||
sensor_readings.append(reading)
|
||||
|
||||
return {
|
||||
"room_metrics": room_metrics,
|
||||
"sensor_readings": sensor_readings
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting room data: {e}")
|
||||
raise
|
||||
|
||||
async def update_room_metrics(self, sensor_data):
|
||||
"""Update room-level metrics when sensor data is received"""
|
||||
try:
|
||||
if not sensor_data.room:
|
||||
return
|
||||
|
||||
# Calculate room-level aggregates
|
||||
room_metrics = await self._calculate_room_metrics(sensor_data.room)
|
||||
|
||||
if room_metrics:
|
||||
# Store room metrics
|
||||
metrics_doc = {
|
||||
"room": sensor_data.room,
|
||||
"timestamp": sensor_data.timestamp,
|
||||
"total_energy": room_metrics.get("total_energy", 0),
|
||||
"average_temperature": room_metrics.get("avg_temperature"),
|
||||
"co2_level": room_metrics.get("co2_level"),
|
||||
"occupancy_estimate": room_metrics.get("occupancy_estimate"),
|
||||
"sensor_count": room_metrics.get("sensor_count", 0),
|
||||
"created_at": datetime.utcnow()
|
||||
}
|
||||
|
||||
await self.db.room_metrics.insert_one(metrics_doc)
|
||||
|
||||
# Cache latest metrics
|
||||
if self.redis:
|
||||
cache_key = f"room:{sensor_data.room}:latest_metrics"
|
||||
await self.redis.setex(cache_key, 3600, json.dumps(metrics_doc, default=str))
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error updating room metrics: {e}")
|
||||
|
||||
async def aggregate_all_room_metrics(self):
|
||||
"""Aggregate metrics for all rooms"""
|
||||
try:
|
||||
# Get all unique rooms
|
||||
pipeline = [{"$group": {"_id": "$room"}}]
|
||||
cursor = self.db.sensors.aggregate(pipeline)
|
||||
|
||||
async for room_data in cursor:
|
||||
room_name = room_data["_id"]
|
||||
if room_name:
|
||||
await self._calculate_room_metrics(room_name)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error aggregating room metrics: {e}")
|
||||
|
||||
async def _get_latest_room_metrics(self, room_name: str) -> Optional[Dict[str, Any]]:
|
||||
"""Get latest room metrics"""
|
||||
try:
|
||||
# Try Redis cache first
|
||||
if self.redis:
|
||||
cache_key = f"room:{room_name}:latest_metrics"
|
||||
cached = await self.redis.get(cache_key)
|
||||
if cached:
|
||||
return json.loads(cached)
|
||||
|
||||
# Fall back to database
|
||||
latest = await self.db.room_metrics.find_one(
|
||||
{"room": room_name},
|
||||
sort=[("timestamp", -1)]
|
||||
)
|
||||
|
||||
if latest:
|
||||
latest["_id"] = str(latest["_id"])
|
||||
return latest
|
||||
|
||||
return None
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting latest room metrics: {e}")
|
||||
return None
|
||||
|
||||
async def _get_recent_room_metrics(self, room_name: str, hours: int = 24) -> List[Dict[str, Any]]:
|
||||
"""Get recent room metrics"""
|
||||
try:
|
||||
start_time = datetime.utcnow() - timedelta(hours=hours)
|
||||
|
||||
cursor = self.db.room_metrics.find({
|
||||
"room": room_name,
|
||||
"created_at": {"$gte": start_time}
|
||||
}).sort("timestamp", -1)
|
||||
|
||||
metrics = []
|
||||
async for metric in cursor:
|
||||
metric["_id"] = str(metric["_id"])
|
||||
metrics.append(metric)
|
||||
|
||||
return metrics
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting recent room metrics: {e}")
|
||||
return []
|
||||
|
||||
async def _calculate_room_metrics(self, room_name: str) -> Dict[str, Any]:
|
||||
"""Calculate aggregated metrics for a room"""
|
||||
try:
|
||||
# Get recent sensor readings (last 5 minutes)
|
||||
five_minutes_ago = datetime.utcnow() - timedelta(minutes=5)
|
||||
|
||||
pipeline = [
|
||||
{
|
||||
"$match": {
|
||||
"room": room_name,
|
||||
"created_at": {"$gte": five_minutes_ago}
|
||||
}
|
||||
},
|
||||
{
|
||||
"$group": {
|
||||
"_id": "$sensor_id",
|
||||
"latest_value": {"$last": "$value"},
|
||||
"sensor_type": {"$last": "$sensor_type"} if "sensor_type" in ["$first", "$last"] else {"$first": "energy"},
|
||||
"unit": {"$last": "$unit"}
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
cursor = self.db.sensor_readings.aggregate(pipeline)
|
||||
|
||||
total_energy = 0
|
||||
temperatures = []
|
||||
co2_levels = []
|
||||
sensor_count = 0
|
||||
|
||||
async for sensor_data in cursor:
|
||||
sensor_count += 1
|
||||
value = sensor_data.get("latest_value", 0)
|
||||
sensor_type = sensor_data.get("sensor_type", "energy")
|
||||
|
||||
if sensor_type == "energy" or "energy" in str(sensor_data.get("unit", "")).lower():
|
||||
total_energy += value
|
||||
elif sensor_type == "temperature":
|
||||
temperatures.append(value)
|
||||
elif sensor_type == "co2":
|
||||
co2_levels.append(value)
|
||||
|
||||
metrics = {
|
||||
"total_energy": total_energy,
|
||||
"sensor_count": sensor_count,
|
||||
"avg_temperature": sum(temperatures) / len(temperatures) if temperatures else None,
|
||||
"co2_level": sum(co2_levels) / len(co2_levels) if co2_levels else None,
|
||||
"occupancy_estimate": self._estimate_occupancy(sensor_count, total_energy)
|
||||
}
|
||||
|
||||
return metrics
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error calculating room metrics: {e}")
|
||||
return {}
|
||||
|
||||
def _estimate_occupancy(self, sensor_count: int, total_energy: float) -> Optional[str]:
|
||||
"""Estimate occupancy level based on energy consumption"""
|
||||
if total_energy == 0:
|
||||
return "vacant"
|
||||
elif total_energy < sensor_count * 50: # Low threshold
|
||||
return "low"
|
||||
elif total_energy < sensor_count * 150: # Medium threshold
|
||||
return "medium"
|
||||
else:
|
||||
return "high"
|
||||
251
microservices/sensor-service/sensor_service.py
Normal file
251
microservices/sensor-service/sensor_service.py
Normal file
@@ -0,0 +1,251 @@
|
||||
"""
|
||||
Sensor service business logic
|
||||
"""
|
||||
|
||||
import logging
|
||||
from datetime import datetime, timedelta
|
||||
from typing import List, Dict, Any, Optional
|
||||
import json
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class SensorService:
|
||||
"""Service for managing sensors and sensor data"""
|
||||
|
||||
def __init__(self, db, redis_client):
|
||||
self.db = db
|
||||
self.redis = redis_client
|
||||
|
||||
async def get_sensors(self, room: Optional[str] = None, sensor_type: Optional[str] = None, status: Optional[str] = None) -> List[Dict[str, Any]]:
|
||||
"""Get sensors with optional filtering"""
|
||||
try:
|
||||
query = {}
|
||||
|
||||
if room:
|
||||
query["room"] = room
|
||||
if sensor_type:
|
||||
query["sensor_type"] = sensor_type
|
||||
if status:
|
||||
query["status"] = status
|
||||
|
||||
cursor = self.db.sensors.find(query)
|
||||
sensors = []
|
||||
|
||||
async for sensor in cursor:
|
||||
sensor["_id"] = str(sensor["_id"])
|
||||
sensors.append(sensor)
|
||||
|
||||
return sensors
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting sensors: {e}")
|
||||
raise
|
||||
|
||||
async def get_sensor_details(self, sensor_id: str) -> Optional[Dict[str, Any]]:
|
||||
"""Get detailed sensor information"""
|
||||
try:
|
||||
sensor = await self.db.sensors.find_one({"sensor_id": sensor_id})
|
||||
|
||||
if sensor:
|
||||
sensor["_id"] = str(sensor["_id"])
|
||||
|
||||
# Get recent readings
|
||||
recent_readings = await self.get_sensor_data(sensor_id, limit=10)
|
||||
sensor["recent_readings"] = recent_readings.get("readings", [])
|
||||
|
||||
return sensor
|
||||
|
||||
return None
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting sensor details: {e}")
|
||||
raise
|
||||
|
||||
async def get_sensor_data(self, sensor_id: str, start_time: Optional[int] = None,
|
||||
end_time: Optional[int] = None, limit: int = 100, offset: int = 0) -> Dict[str, Any]:
|
||||
"""Get historical sensor data"""
|
||||
try:
|
||||
query = {"sensor_id": sensor_id}
|
||||
|
||||
if start_time or end_time:
|
||||
query["timestamp"] = {}
|
||||
if start_time:
|
||||
query["timestamp"]["$gte"] = start_time
|
||||
if end_time:
|
||||
query["timestamp"]["$lte"] = end_time
|
||||
|
||||
# Get total count
|
||||
total_count = await self.db.sensor_readings.count_documents(query)
|
||||
|
||||
# Get readings
|
||||
cursor = self.db.sensor_readings.find(query).sort("timestamp", -1).skip(offset).limit(limit)
|
||||
readings = []
|
||||
|
||||
async for reading in cursor:
|
||||
reading["_id"] = str(reading["_id"])
|
||||
readings.append(reading)
|
||||
|
||||
return {
|
||||
"readings": readings,
|
||||
"total_count": total_count,
|
||||
"execution_time_ms": 0 # Placeholder
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting sensor data: {e}")
|
||||
raise
|
||||
|
||||
async def create_sensor(self, sensor_data) -> Dict[str, Any]:
|
||||
"""Create a new sensor"""
|
||||
try:
|
||||
# Check if sensor already exists
|
||||
existing = await self.db.sensors.find_one({"sensor_id": sensor_data.sensor_id})
|
||||
if existing:
|
||||
raise ValueError(f"Sensor {sensor_data.sensor_id} already exists")
|
||||
|
||||
# Create sensor document
|
||||
sensor_doc = {
|
||||
"sensor_id": sensor_data.sensor_id,
|
||||
"name": sensor_data.name,
|
||||
"sensor_type": sensor_data.sensor_type.value if hasattr(sensor_data.sensor_type, 'value') else str(sensor_data.sensor_type),
|
||||
"room": sensor_data.room,
|
||||
"location": sensor_data.location if hasattr(sensor_data, 'location') else None,
|
||||
"status": "active",
|
||||
"created_at": datetime.utcnow(),
|
||||
"updated_at": datetime.utcnow()
|
||||
}
|
||||
|
||||
result = await self.db.sensors.insert_one(sensor_doc)
|
||||
|
||||
return {"created_at": datetime.utcnow()}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error creating sensor: {e}")
|
||||
raise
|
||||
|
||||
async def update_sensor(self, sensor_id: str, update_data: Dict[str, Any]) -> bool:
|
||||
"""Update sensor metadata"""
|
||||
try:
|
||||
update_data["updated_at"] = datetime.utcnow()
|
||||
|
||||
result = await self.db.sensors.update_one(
|
||||
{"sensor_id": sensor_id},
|
||||
{"$set": update_data}
|
||||
)
|
||||
|
||||
return result.modified_count > 0
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error updating sensor: {e}")
|
||||
raise
|
||||
|
||||
async def delete_sensor(self, sensor_id: str) -> Dict[str, Any]:
|
||||
"""Delete a sensor and its data"""
|
||||
try:
|
||||
# Delete readings
|
||||
readings_result = await self.db.sensor_readings.delete_many({"sensor_id": sensor_id})
|
||||
|
||||
# Delete sensor
|
||||
await self.db.sensors.delete_one({"sensor_id": sensor_id})
|
||||
|
||||
return {"readings_deleted": readings_result.deleted_count}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error deleting sensor: {e}")
|
||||
raise
|
||||
|
||||
async def ingest_sensor_data(self, sensor_data) -> Dict[str, Any]:
|
||||
"""Ingest real-time sensor data"""
|
||||
try:
|
||||
# Create reading document
|
||||
reading_doc = {
|
||||
"sensor_id": sensor_data.sensor_id,
|
||||
"timestamp": sensor_data.timestamp,
|
||||
"value": sensor_data.value,
|
||||
"unit": sensor_data.unit if hasattr(sensor_data, 'unit') else None,
|
||||
"room": sensor_data.room if hasattr(sensor_data, 'room') else None,
|
||||
"created_at": datetime.utcnow()
|
||||
}
|
||||
|
||||
# Store in database
|
||||
await self.db.sensor_readings.insert_one(reading_doc)
|
||||
|
||||
# Cache recent value in Redis
|
||||
if self.redis:
|
||||
cache_key = f"sensor:{sensor_data.sensor_id}:latest"
|
||||
await self.redis.setex(cache_key, 3600, json.dumps(reading_doc, default=str))
|
||||
|
||||
return {"success": True}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error ingesting sensor data: {e}")
|
||||
raise
|
||||
|
||||
async def export_data(self, start_time: int, end_time: int, sensor_ids: Optional[str] = None,
|
||||
format: str = "json") -> Dict[str, Any]:
|
||||
"""Export sensor data"""
|
||||
try:
|
||||
query = {
|
||||
"timestamp": {"$gte": start_time, "$lte": end_time}
|
||||
}
|
||||
|
||||
if sensor_ids:
|
||||
sensor_list = [s.strip() for s in sensor_ids.split(",")]
|
||||
query["sensor_id"] = {"$in": sensor_list}
|
||||
|
||||
cursor = self.db.sensor_readings.find(query).sort("timestamp", 1)
|
||||
readings = []
|
||||
|
||||
async for reading in cursor:
|
||||
reading["_id"] = str(reading["_id"])
|
||||
readings.append(reading)
|
||||
|
||||
return {
|
||||
"format": format,
|
||||
"data": readings,
|
||||
"total_records": len(readings),
|
||||
"period": {"start": start_time, "end": end_time}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error exporting data: {e}")
|
||||
raise
|
||||
|
||||
async def get_events(self, severity: Optional[str] = None, event_type: Optional[str] = None,
|
||||
hours: int = 24, limit: int = 50) -> List[Dict[str, Any]]:
|
||||
"""Get system events"""
|
||||
try:
|
||||
start_time = datetime.utcnow() - timedelta(hours=hours)
|
||||
|
||||
query = {"timestamp": {"$gte": start_time}}
|
||||
|
||||
if severity:
|
||||
query["severity"] = severity
|
||||
if event_type:
|
||||
query["event_type"] = event_type
|
||||
|
||||
cursor = self.db.system_events.find(query).sort("timestamp", -1).limit(limit)
|
||||
events = []
|
||||
|
||||
async for event in cursor:
|
||||
event["_id"] = str(event["_id"])
|
||||
events.append(event)
|
||||
|
||||
return events
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting events: {e}")
|
||||
return []
|
||||
|
||||
async def cleanup_old_data(self, cutoff_date: datetime):
|
||||
"""Clean up old sensor data"""
|
||||
try:
|
||||
result = await self.db.sensor_readings.delete_many({
|
||||
"created_at": {"$lt": cutoff_date}
|
||||
})
|
||||
|
||||
logger.info(f"Cleaned up {result.deleted_count} old sensor readings")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error cleaning up old data: {e}")
|
||||
raise
|
||||
Reference in New Issue
Block a user