# Use Cases

## Use Cases for the *Forecast App*

The *Forecast App* can be used in numerous practical scenarios where the goal is to predict future values based on historical measured data. Below you will find typical use cases with a description of the objective, the recommended configuration, and possible extensions.

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### 1. **Predict Energy Consumption**

**Objective:** Forecast future electricity, gas, or water consumption on an hourly or daily basis to optimize energy procurement and to detect anomalies early.

**Example Configuration:**

* **Asset:** Meter (e.g., electricity meter)
* **Target Attribute:** Energy consumption (difference value, not the meter reading)
* **Feature Attributes:** `hour_of_day`, `day_of_week`, outdoor temperature (optional)
* **Forecast Length:** 24 (for 24 hours)
* **Context Length:** 168 (one week as context)

**Extensions:**

* Visualization in the dashboard
* Automatic comparison with planned values from the *Calculator*

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### 2. **Regulate Indoor Temperature**

**Objective:** Predict room temperature for the optimal control of heating, ventilation, or cooling.

**Example Configuration:**

* **Asset:** Room climate sensor
* **Target Attribute:** Temperature
* **Feature Attributes:** `hour_of_day`, `day_of_week`, current window position, or CO₂ values
* **Forecast Length:** 12 (for the next 12 time units)
* **Context Length:** 48–72

**Extensions:**

* Combination with rule engine to automate building control
* Alerts when planned limits are exceeded or fallen short of

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### 3. **Monitor Humidity**

**Objective:** Early detection of potential moisture problems by predicting humidity in critical areas.

**Example Configuration:**

* **Asset:** Sensor in a technical room, archive, warehouse, etc.
* **Target Attribute:** Humidity
* **Feature Attributes:** `hour_of_day`, temperature, air exchange rate (optional)
* **Forecast Length:** 6
* **Context Length:** 24

**Extensions:**

* Integration with alarm system
* Link with ventilation control

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### 4. **Forecast Occupancy of Meeting Rooms**

**Objective:** Recognize recurring usage patterns for better room planning.

**Example Configuration:**

* **Asset:** Presence sensor or occupancy status
* **Target Attribute:** Occupancy (0 or 1)
* **Feature Attributes:** `hour_of_day`, `day_of_week`
* **Forecast Length:** 48 (e.g., for the next two days)
* **Context Length:** 96

**Extensions:**

* Link with *Booking Widget*
* Display of free periods on digital door signs

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### 5. **Detect Technical Anomalies**

**Objective:** Indirect prediction of malfunctions, for example, in ventilation, pumps, or servers—e.g., due to temperature increase or altered power consumption.

**Example Configuration:**

* **Asset:** Technical component with sensors
* **Target Attribute:** Operating temperature or power consumption
* **Feature Attributes:** `hour_of_day`, current load, outdoor temperature
* **Forecast Length:** 6
* **Context Length:** 72