---
license: apache-2.0
task_categories:
- text-classification
language:
- en
tags:
- networking
- wifi
- cybersecurity
- synthetic-data
- connected-home
pretty_name: SmartNet Network Incidents
size_categories:
- 1K<n<10K
---

# SmartNet Network Incidents

## Dataset description

SmartNet Network Incidents is a synthetic dataset for experimenting with
classification of connected-home networking and security incidents.

Each record combines structured telemetry with a short natural-language
incident description.

## Supported tasks

- Network incident classification
- Support-ticket triage
- Explainable troubleshooting demonstrations
- Retrieval and RAG experiments
- Model-serving and observability demonstrations

## Labels

| Label | Meaning |
|---|---|
| `healthy` | No material network problem detected |
| `weak_signal` | Poor Wi-Fi signal or excessive distance/attenuation |
| `wifi_congestion` | Heavy channel utilization or interference |
| `high_latency` | Elevated latency or packet loss |
| `dhcp_failure` | Address allocation or lease-renewal problem |
| `dns_security_risk` | Suspicious or unusually risky DNS behaviour |

## Fields

| Field | Type | Description |
|---|---|---|
| `incident_id` | string | Synthetic record identifier |
| `timestamp` | string | Synthetic UTC timestamp |
| `device_type` | string | Device category |
| `rssi_dbm` | integer | Received signal strength |
| `channel_utilization_pct` | integer | Wi-Fi channel utilization |
| `latency_ms` | integer | Observed network latency |
| `packet_loss_pct` | float | Estimated packet loss |
| `dhcp_failures` | integer | Recent DHCP failures |
| `dns_risk_score` | float | Synthetic DNS risk score |
| `incident_text` | string | Natural-language incident summary |
| `label` | string | Target incident category |

## Data generation

The records are generated programmatically with deterministic random seeds,
label-specific telemetry ranges, varied text templates, and small amounts of
noise. No customer records, personal data, or production telemetry are used.

## Intended use

This dataset is intended for education, portfolio demonstrations, prototyping,
testing pipelines, and comparing classification approaches.

## Limitations

- The data is synthetic.
- Labels originate from generation rules rather than human annotation.
- Reported model scores may overestimate real-world performance.
- The dataset does not represent every router, client, environment, or attack.
- It must not be used for safety-critical or production security decisions
  without validation on representative real-world data.

## Privacy

The dataset contains no real users, addresses, identifiers, or customer
telemetry.