IVMS Automated Reporting Software Development -- 2
Budget: $10 – $30 USD
Automated IVMS Reporting Platform
Proposal and Scope of Work
This proposal defines the scope of work for the design, development, and implementation of an Automated IVMS Reporting Platform.
The platform will automate the preparation of the Santos Weekly Exception Report, Staff Weekly KM YTD Report, and Staff Risk Management Report. It will retain the existing approved reporting logic while improving data accuracy, automation, validation, presentation, and management reporting.
Master System Technologies will provide access to the On-Road IoT API, including the required credentials, documentation, endpoints, and available data fields.
1. Overview
The platform will provide a centralised view of:
* Driver exception events.
* Distance travelled and trip activity.
* Driver exposure.
* Vehicle utilisation.
* Driver risk behaviour.
* Weekly and monthly performance.
Data will be retrieved primarily through the On-Road IoT API, with support for CSV and Excel uploads where required.
2. Objectives
* Automate weekly IVMS reporting.
* Reduce manual spreadsheet processing.
* Maintain accurate Month-to-Date totals.
* Combine exception, KM, trip, and driver-risk data.
* Standardise driver, department, reporting group, date, and event information.
* Remove duplicate, invalid, and excluded records.
* Correctly separate cross-month reporting periods.
* Preserve historical reports and approved formats.
* Produce management-ready reports with minimal manual input.
3. Data Sources
3.1 On-Road IoT API
The platform will connect securely to the On-Road IoT API to retrieve available data such as:
* Driver and employee details.
* Vehicle and asset information.
* Reporting groups.
* Trip and kilometre data.
* Exception events.
* Event dates, times, durations, and locations.
* Speed limits and actual speeds.
* GPS coordinates.
* Speeding, fatigue, seatbelt, harsh-driving, and after-hours events.
The final integration will depend on the API fields, authentication method, rate limits, refresh frequency, and historical data availability.
3.2 Supporting Data
The platform may also use:
* CSV and Excel source files.
* Santos reporting templates.
* Driver and employee master data.
* Department and reporting group mappings.
* Location reference files.
* Historical reporting workbooks.
* Approved business and consolidation rules.
4. Functional Scope
4.1 Weekly Exception Reporting
The platform will:
* Retrieve or import exception data.
* Validate and map source fields into the approved Santos format.
* Standardise exception names and descriptions.
* Remove speeding events that are 5 km/h or less above the posted limit.
* Retain speeding events that are 6 km/h or more above the posted limit.
* Consolidate repeated events only where they involve the same vehicle, location, exception rule, date, and occur within the approved 60-second timing rule.
* Complete missing employee and department information.
* Convert employee numbers to uppercase.
* Populate coordinates where a valid location match is available.
* Generate the Weekly Exception Report.
4.2 Weekly KM Reporting
The platform will:
* Retrieve or import trip and kilometre data.
* Remove blank rows, invalid trips, and duplicates.
* Standardise driver names, dates, times, and reporting groups.
* Consolidate duplicate driver records.
* Sum kilometres by driver.
* Assign missing reporting groups as **No updated department**.
* Exclude **Unknown Driver** records.
* Generate cumulative Month-to-Date totals.
* Preserve historical report structures.
4.3 Monthly and Cross-Month Logic
Weekly data will accumulate into the correct calendar month.
Where a reporting period crosses two months, records will be split by date. For example:
* 27–30 April will be added to April.
* 1–3 May will be added to May.
Finalised historical months will not be overwritten.
4.4 Staff Risk Management Reporting
The combined report will include:
* Driver name and reporting group.
* Distance travelled.
* Driving and idle duration.
* Vehicle utilisation.
* Speeding, fatigue, seatbelt, harsh-driving, and after-hours events.
* Total exception counts.
* Weekly updates.
* Monthly cumulative totals.
* Driver risk and performance trends.
4.5 Data Completion Rules
* Department available but employee number missing: **CONTRACTOR**.
* Employee number available but department missing: **No updated department**.
* Both missing: employee number **NEW** and department **No updated department**.
* All employee numbers will be converted to uppercase.
* Missing coordinates will be populated where a valid reference match exists.
5. User Interface
The platform will provide:
* Web-based desktop and tablet access.
* API synchronisation controls.
* File upload where required.
* Weekly and monthly report selection.
* Filters by driver, vehicle, department, reporting group, date, and exception type.
* Driver-level drill-down.
* Colour-coded risk indicators.
* Historical trend views.
* Excel and PDF export.
* Clear processing and validation messages.
6. Data Validation and Security
The system will:
* Securely store API credentials.
* Prevent duplicate imports and processing.
* Validate totals and cross-month allocation.
* Reconcile KM and exception totals against source data.
* Maintain an audit trail.
* Apply role-based access.
* Protect historical reports.
* Perform regular database and file backups.
7. Deliverables
* Functional Specification Document.
* On-Road IoT API integration.
* Automated IVMS reporting platform.
* Weekly Exception Report.
* Staff Weekly KM YTD Report.
* Staff Risk Management Report.
* Cleaned exception and trip datasets.
* Validation and duplicate logs.
* Automated Month-to-Date and cross-month processing.
* Dashboard prototype.
* Final production platform.
* Editable source code.
* Technical documentation.
* User guide and Standard Operating Procedures.
* Testing, training, and support plan.
8. Project Timeline
The indicative timeline is four to six weeks:
* Requirements and API review – 1 week.
* Data mapping and business rules – 1 week.
* Design and prototype – 1 week.
* API integration and development – 1 weeks.
* Testing and User Acceptance Testing – 1 week.
* Deployment and training – 1 week.
9. Future Expansion Options
* Scheduled automatic API synchronisation.
* Automated weekly email distribution.
* SQL and Power BI integration.
* Driver risk scoring.
* Geofence reporting.
* Predictive risk analysis.
* Additional reports, clients, and KPIs.
* Mobile reporting and management alerts.
10. Summary
The Automated IVMS Reporting Platform will combine weekly exception reporting, kilometre reporting, and staff risk management into one central solution.
Using the On-Road IoT API, the platform will automate data retrieval, cleaning, driver matching, event filtering, monthly accumulation, cross-month separation, validation, and report generation.
The solution will reduce manual work, improve reporting accuracy, preserve historical information, and provide management with a consolidated view of driver exposure, vehicle utilisation, exception behaviour, and risk performance.
Proposal and Scope of Work
This proposal defines the scope of work for the design, development, and implementation of an Automated IVMS Reporting Platform.
The platform will automate the preparation of the Santos Weekly Exception Report, Staff Weekly KM YTD Report, and Staff Risk Management Report. It will retain the existing approved reporting logic while improving data accuracy, automation, validation, presentation, and management reporting.
Master System Technologies will provide access to the On-Road IoT API, including the required credentials, documentation, endpoints, and available data fields.
1. Overview
The platform will provide a centralised view of:
* Driver exception events.
* Distance travelled and trip activity.
* Driver exposure.
* Vehicle utilisation.
* Driver risk behaviour.
* Weekly and monthly performance.
Data will be retrieved primarily through the On-Road IoT API, with support for CSV and Excel uploads where required.
2. Objectives
* Automate weekly IVMS reporting.
* Reduce manual spreadsheet processing.
* Maintain accurate Month-to-Date totals.
* Combine exception, KM, trip, and driver-risk data.
* Standardise driver, department, reporting group, date, and event information.
* Remove duplicate, invalid, and excluded records.
* Correctly separate cross-month reporting periods.
* Preserve historical reports and approved formats.
* Produce management-ready reports with minimal manual input.
3. Data Sources
3.1 On-Road IoT API
The platform will connect securely to the On-Road IoT API to retrieve available data such as:
* Driver and employee details.
* Vehicle and asset information.
* Reporting groups.
* Trip and kilometre data.
* Exception events.
* Event dates, times, durations, and locations.
* Speed limits and actual speeds.
* GPS coordinates.
* Speeding, fatigue, seatbelt, harsh-driving, and after-hours events.
The final integration will depend on the API fields, authentication method, rate limits, refresh frequency, and historical data availability.
3.2 Supporting Data
The platform may also use:
* CSV and Excel source files.
* Santos reporting templates.
* Driver and employee master data.
* Department and reporting group mappings.
* Location reference files.
* Historical reporting workbooks.
* Approved business and consolidation rules.
4. Functional Scope
4.1 Weekly Exception Reporting
The platform will:
* Retrieve or import exception data.
* Validate and map source fields into the approved Santos format.
* Standardise exception names and descriptions.
* Remove speeding events that are 5 km/h or less above the posted limit.
* Retain speeding events that are 6 km/h or more above the posted limit.
* Consolidate repeated events only where they involve the same vehicle, location, exception rule, date, and occur within the approved 60-second timing rule.
* Complete missing employee and department information.
* Convert employee numbers to uppercase.
* Populate coordinates where a valid location match is available.
* Generate the Weekly Exception Report.
4.2 Weekly KM Reporting
The platform will:
* Retrieve or import trip and kilometre data.
* Remove blank rows, invalid trips, and duplicates.
* Standardise driver names, dates, times, and reporting groups.
* Consolidate duplicate driver records.
* Sum kilometres by driver.
* Assign missing reporting groups as **No updated department**.
* Exclude **Unknown Driver** records.
* Generate cumulative Month-to-Date totals.
* Preserve historical report structures.
4.3 Monthly and Cross-Month Logic
Weekly data will accumulate into the correct calendar month.
Where a reporting period crosses two months, records will be split by date. For example:
* 27–30 April will be added to April.
* 1–3 May will be added to May.
Finalised historical months will not be overwritten.
4.4 Staff Risk Management Reporting
The combined report will include:
* Driver name and reporting group.
* Distance travelled.
* Driving and idle duration.
* Vehicle utilisation.
* Speeding, fatigue, seatbelt, harsh-driving, and after-hours events.
* Total exception counts.
* Weekly updates.
* Monthly cumulative totals.
* Driver risk and performance trends.
4.5 Data Completion Rules
* Department available but employee number missing: **CONTRACTOR**.
* Employee number available but department missing: **No updated department**.
* Both missing: employee number **NEW** and department **No updated department**.
* All employee numbers will be converted to uppercase.
* Missing coordinates will be populated where a valid reference match exists.
5. User Interface
The platform will provide:
* Web-based desktop and tablet access.
* API synchronisation controls.
* File upload where required.
* Weekly and monthly report selection.
* Filters by driver, vehicle, department, reporting group, date, and exception type.
* Driver-level drill-down.
* Colour-coded risk indicators.
* Historical trend views.
* Excel and PDF export.
* Clear processing and validation messages.
6. Data Validation and Security
The system will:
* Securely store API credentials.
* Prevent duplicate imports and processing.
* Validate totals and cross-month allocation.
* Reconcile KM and exception totals against source data.
* Maintain an audit trail.
* Apply role-based access.
* Protect historical reports.
* Perform regular database and file backups.
7. Deliverables
* Functional Specification Document.
* On-Road IoT API integration.
* Automated IVMS reporting platform.
* Weekly Exception Report.
* Staff Weekly KM YTD Report.
* Staff Risk Management Report.
* Cleaned exception and trip datasets.
* Validation and duplicate logs.
* Automated Month-to-Date and cross-month processing.
* Dashboard prototype.
* Final production platform.
* Editable source code.
* Technical documentation.
* User guide and Standard Operating Procedures.
* Testing, training, and support plan.
8. Project Timeline
The indicative timeline is four to six weeks:
* Requirements and API review – 1 week.
* Data mapping and business rules – 1 week.
* Design and prototype – 1 week.
* API integration and development – 1 weeks.
* Testing and User Acceptance Testing – 1 week.
* Deployment and training – 1 week.
9. Future Expansion Options
* Scheduled automatic API synchronisation.
* Automated weekly email distribution.
* SQL and Power BI integration.
* Driver risk scoring.
* Geofence reporting.
* Predictive risk analysis.
* Additional reports, clients, and KPIs.
* Mobile reporting and management alerts.
10. Summary
The Automated IVMS Reporting Platform will combine weekly exception reporting, kilometre reporting, and staff risk management into one central solution.
Using the On-Road IoT API, the platform will automate data retrieval, cleaning, driver matching, event filtering, monthly accumulation, cross-month separation, validation, and report generation.
The solution will reduce manual work, improve reporting accuracy, preserve historical information, and provide management with a consolidated view of driver exposure, vehicle utilisation, exception behaviour, and risk performance.