electricsheepafrica/nigerian-telecom-artificial-intelligence-automation-dataset

Artificial Intelligence Automation Dataset

Dataset Description

Self-optimizing network operations with AI recommendations and outcomes

Dataset Information

• Category: Emerging and Advanced
• Format: CSV, Parquet
• Rows: 150,000
• Columns: 16
• Date Generated: 2025-10-05
• Location: data/artificial_intelligence_automation_dataset/

Schema

Column	Type	Sample Values
automation_id	String	AI00000001
timestamp	Datetime	2025-09-11 16:14:00
tower_id	String	ONI-2064
city	String	Onitsha
optimization_type	String	power_optimization
ai_model	String	neural_network
ai_recommendation	String	decrease
confidence_score	Float	0.83
action_taken	Boolean	True
performance_before_percent	Float	82.58
performance_after_percent	Float	97.32
improvement_percent	Float	14.74
energy_saved_kwh	Float	186.49
users_impacted	Integer	1489
operator	String	9mobile
automation_status	String	success

Sample Data

automation_id           timestamp tower_id    city  optimization_type               ai_model ai_recommendation  confidence_score  action_taken  performance_before_percent  performance_after_percent  improvement_percent  energy_saved_kwh  users_impacted operator automation_status
   AI00000001 2025-09-11 16:14:00 ONI-2064 Onitsha power_optimization         neural_network          decrease              0.83          True                       82.58                      97.32                14.74            186.49            1489  9mobile           success
   AI00000002 2025-09-20 17:22:00 ENU-2233   Enugu   fault_prediction         neural_network          decrease              0.80          True                       78.46                      87.60                 9.14              0.00            3158      MTN            failed
   AI00000003 2025-09-09 12:12:00 KAD-3174  Kaduna      energy_saving reinforcement_learning      redistribute              0.86          True                       62.16                      62.16                11.30             11.69            4299      Glo            failed

Nigerian Context

This dataset incorporates authentic Nigerian telecommunications characteristics:

• Geographic Coverage: Major Nigerian cities including Lagos, Abuja, Kano, Port Harcourt, Ibadan
• Operators: MTN, Airtel, Glo, 9mobile with realistic market shares
• Phone Numbers: Nigerian format (+234 prefixes)
• Currency: Nigerian Naira (NGN)
• Time Zone: West Africa Time (WAT, UTC+1)
• Network Types: 2G, 3G, 4G, 5G distribution

File Formats

CSV

data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.csv

Parquet (Recommended)

data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.parquet

Loading the Dataset

Python (Pandas)

import pandas as pd

# Load CSV
df = pd.read_csv('data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.csv')

# Load Parquet (recommended for large datasets)
df = pd.read_parquet('data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.parquet')

Python (PyArrow)

import pyarrow.parquet as pq

# Load Parquet
table = pq.read_table('data/artificial_intelligence_automation_dataset/artificial_intelligence_automation_dataset.parquet')
df = table.to_pandas()

License

MIT License - For educational and research purposes

Citation

Nigerian Telecom Datasets - Artificial Intelligence Automation Dataset
Generated: 2025-10-05
Category: Emerging and Advanced
Rows: 150,000

Related Datasets

This dataset is part of the Nigerian Telecom Datasets collection, which includes 34 datasets covering network performance, customer behavior, financial transactions, infrastructure, geospatial data, customer experience, and emerging technologies.