Eye4.ai
From Challenges to Discover how our smart solutions drive real impact across industries. From optimizing operations to enhancing efficiency, explore innovative use cases that solve real-world challenges. |
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Asset Optimisation
Unit Level Device & Divestment Trays
02
Real-Time Queue Intelligence
Queue Counts & Crowd Flow Monitoring
03
Predict Bus Arrival Insights
Accurate ETA Tracking for smarter Commuting
Customer Use Cases 1
Unit Level Device and
Divestment Trays
The Pain Points
01
Long Wait
Times & Queues
Poor queue management causing delays and dissatisfaction.
02
Lack of Operational Insights
Video analytics revealed inefficiencies and improved decisions.
03
Inefficient Storage Management
Video analytics optimized storage use and compliance.
04
Safety Risks from Storage Issues
Video analytics stopped unauthorized storage and enhanced safety.
Strategic
Outcomes
Optimized Queue Management
Video analytics optimized queues, reducing wait times.
Data-Driven Performance Insights
Identified inefficiencies and improved decisions.
Smart Storage Utilization
Video analytics optimized storage and compliance.
Enhanced Safety Compliance
Prevented unauthorized storage and enhanced safety.
Customer Use Cases 2
Queue Counts & Crowd
Flow Monitoring
The Pain Points
01
Lack of Real-Time Visibility
Buses failing to arrive on schedule, causing passenger delays.
02
Inefficient Resource Allocation
Difficult to optimize staffing and workflows without accurate queue data.
03
Operational Blind
Spots
Unidentified peak congestion causes delays and inefficiencies.
04
Customer Experience Impact
Long wait times reduced passenger satisfaction and service quality.
Our Smart
Solutions
Automated Queue Monitoring
Implemented Video Analytics to continuously track queue lengths.
Data-Driven Process Optimization
Implemented Video Analytics to continuously track queue lengths.
Smarter Staffing Adjustments
Optimized resource allocation with real-time queue data.
Enhanced Passenger Flow Management
Optimized peak congestion for a better experience.
Customer Use Cases 3
Bus Arrival Time Monitoring
The Pain Points
01
Unreliable Bus Arrival Times
Buses failing to arrive on schedule, causing passenger delays.
02
Lack of Visibility & Accountability
Hard to optimize staffing without accurate queue data.
03
Inaccurate GPS Tracking
Existing GPS systems failed to provide precise real-time location data.
04
Absence of
Real-Time Insights
No live monitoring system to detect congestion or vehicle dwell times.
Advance AI – Powered
Solution
AI-Powered Vision Analytics
Implemented video analytics to continuously track queue lengths.
Machine Learning for Dwell Time & Congestion
Enhanced crowd management using predictive analytics.
Real-Time Alerts & Dashboards
Optimized resource allocation with real-time queue data.
API-Based Data Integration
Seamless connectivity with existing infrastructure for better insights.
Success Metrics
98%
delivered accurate reports on bus movements.
Reduction in complaints and delays
Video Analytics
The use of existing CCTV cameras proved to be a very efficient way of obtaining valuable real-time data.
Dashboards & Alerting
Supervisors were empowered with real-time dashboards and alerting. This enabled supervisors to take actions that drove the right behaviors.
Success Metrics
98%
delivered accurate reports on bus movements.
Video Analytics
The use of existing CCTV cameras proved to be a very efficient way of obtaining valuable real-time data.
Dashboards & Alerting
Supervisors were empowered with real-time dashboards and alerting.
This enabled supervisors to take actions that drove the right behaviors.
Reduction in complaints and delays
Customer Use Cases 4
Bathroom Cleaning Optimisation
The Pain Points
01
High Cleaning
Costs
Continuous cleaning of 60 bathrooms 24/7 resulted in $XXM annual costs.
02
Lack of Data for Optimization
No insights on peak usage times or bathroom utilization patterns.
03
Inefficient Resource Allocation
Cleaning schedules didn’t match demand, causing extra costs.
04
Camera
Limitations
Bad camera angles and lighting reduced Video Analytics accuracy.
Transformative
Actions
Data-Driven Cleaning Strategy
Video analytics linked gate allocation to bathroom usage.
Resource Optimization
Insights enabled smarter scheduling based on real-time usage patterns.
Technology-Driven Improvements
Findings drove investment in advanced analytics.
Overcoming Limitations
Optimizing camera placement and lighting for accuracy.
