Objective:

Assist the company in optimising its cellular antenna stations.

Solution:

Conduct a comprehensive big data analysis to reduce costs and predict maintenance actions, including location and timing.

Actions:

• Analyse data from thousands of IoT sensors, incidents, fuel refills, solar energy generation, and preventive maintenance checks.

• Use this data to identify patterns and optimise maintenance schedules and operational efficiency.

• Data loading, processing, and normalisation.

• Ensure that data from various sources is cleaned, standardised, and prepared for analysis to support accurate decision-making.

Actions:

• Visualise analysis summaries using interactive charts:

• Consumption patterns

-Deviations. Relationships. Anomalies

Provide intuitive and dynamic dashboards to identify key insights and trends.

• Descriptive analysis: Analyse station data to understand what has happened and why, identifying trends, causes of incidents, and past performance.

• Prescriptive analysis: Recommend actions to optimise operations, such as adjustments in maintenance schedules or resource allocation.

• Predictive analysis: Based on historical data and trends, forecast future events, such as when a station will need maintenance or face potential issues.