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UK based Logistics firm migrates to VoIP from BT Landline
The web portal facilitates premium chauffeur services for airport transfers across the UK, specializing in London airports like Heathrow, Gatwick, Stansted, City, Luton, and Southampton.
Industry : Logistics
Key Features:
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Booking Functionality: Users can easily input pickup/drop-off locations, date, and time, with options for vehicle selection.
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Price Algorithm Based on Distance: Fares are calculated transparently based on distance, traffic, tolls, and time.
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Driver Assignment and Ride Tracking: The system assigns nearby drivers automatically and allows real-time ride tracking.
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Payments and Accounts: Secure online payments are integrated, and users can manage bookings and payments through accounts.
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Analytics and Reporting: The portal provides analytics on bookings, revenue, and customer feedback for business insights.
Challenges Faced:
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Accessing VoIP Call Details: Integrating VoIP call details into a web-based system posed challenges in data synchronization, compatibility, and real-time updates.
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Interactive UI/UX Design: Designing an interactive and user-friendly interface for seamless input on different devices, ensuring responsiveness and accessibility.
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Driver UI App and Notifications: Developing an easy-to-use UI for drivers on mobile devices, along with implementing notification features for job alerts and updates.
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Google Location APIs and Algorithms: Implementing Google Maps APIs for accurate location tracking, along with developing algorithms for distance calculations and pricing based on location.
Solutions Implemented:
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API Integration: Utilized VoIP APIs for accessing call details and integrated them into the web-based system for real-time data updates and synchronization.
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User-Centric Design: Employed UX/UI best practices, responsive design frameworks, and user testing to create an interactive and intuitive interface for input on various devices..
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Driver App Development: Designed a simplified UI for the driver app, integrated with notification APIs for job alerts, and optimized for easy navigation and updates.
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Google Maps Integration: Integrated Google Location APIs for accurate location tracking, developed custom algorithms for distance calculations, and implemented dynamic pricing logic based on location and other factors.
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Exact Location Picking: Achieving precise location accuracy, especially in urban areas with GPS signal interference. Employed a combination of GPS, Wi-Fi positioning, and cellular network triangulation for enhanced accuracy.
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Algorithm to Find People in Defined Range: Developing an efficient algorithm to identify nearby users within a specified radius. Implemented a proximity search algorithm using geospatial indexing techniques like R-tree, optimized for scalability and performance.
Challenges Faced and Solutions Implemented:
Data Integration and Consolidation::
Managing multiple decentralized databases led to data silos, inconsistencies, and difficulties in generating unified reports.
Solution: By creating a centralized database on AWS, all data sources were integrated and consolidated into a single repository. This allowed for better data management, improved accuracy in reporting, and streamlined operations.
Scalability and Performance :
The existing decentralized setup lacked scalability, leading to performance issues during peak loads.
Solution: AWS’s scalable infrastructure provided the necessary computing resources to handle increased workloads seamlessly. This ensured optimal performance even during periods of high demand, enhancing user experience and system reliability.
Data Security and Compliance:
With decentralized databases, ensuring data security and regulatory compliance across multiple locations was challenging..
Solution: AWS’s robust security features, including encryption, access controls, and compliance certifications (such as PCI DSS for payment data), were implemented to safeguard sensitive information and meet regulatory requirements.
Migration Complexity:
Migrating data from multiple decentralized databases to a centralized database on AWS required careful planning and execution.
Solution: A phased migration approach was adopted, involving data mapping, cleansing, and validation processes. Tools and services provided by AWS, such as AWS Database Migration Service (DMS), were utilized to streamline the migration process and minimize downtime.
Training and Change Management:
Transitioning from a decentralized to a centralized database model required training agents and staff on new processes and systems.
Solution: Comprehensive training programs and documentation were provided to educate users about the benefits of the centralized database and how to effectively use the AWS platform. Change management strategies were employed to facilitate a smooth transition and ensure user adoption.