AI Agents · Lesson

Automated Response to Sensor Events

If temperature > threshold → alert → actuate: agent-driven IoT control loops.

Automated Event-Driven Agent Responses

When a sensor crosses a threshold, the agent must respond automatically without human intervention. The core challenges: deciding what action to take, ensuring the same event does not trigger duplicate actions, and respecting a cool-down period so the agent does not flood actuators with commands.

Defining Action Policies

An action policy maps sensor conditions to agent responses. Define policies declaratively so they are easy to read and modify without touching logic code. Each policy has a condition, priority, and one or more actions.

ACTION_POLICIES = [
    {
        'name': 'HIGH_TEMP_ALERT',
        'topic': 'sensors/temperature',
        'condition': lambda v: v > 38,
        'priority': 'critical',
        'actions': ['TURN_ON_COOLING', 'ALERT_MAINTENANCE', 'LOG_EVENT']
    },
    {
        'name': 'HIGH_TEMP_WARNING',
        'topic': 'sensors/temperature',
        'condition': lambda v: 35 < v <= 38,
        'priority': 'warning',
        'actions': ['ALERT_MAINTENANCE', 'LOG_EVENT']
    },
    {
        'name': 'LOW_HUMIDITY',
        'topic': 'sensors/humidity',
        'condition': lambda v: v < 30,
        'priority': 'warning',
        'actions': ['TURN_ON_HUMIDIFIER', 'LOG_EVENT']
    }
]

def match_policies(topic: str, value: float) -> list:
    return [
        p for p in ACTION_POLICIES
        if p['topic'] == topic and p['condition'](value)
    ]

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