NCERT books
inventory management.

1. Project Context & Industry Background

Educational publishing directories and national councils manage massive logistics and warehousing networks. Millions of school textbooks must be printed, cataloged, stored, and distributed to thousands of schools, bookstores, and regional distribution centers before the start of each academic year. Unlike standard commercial logistics, educational publishing deals with high SKU volumes (divided by subject, language, grade level, and curriculum year) that must follow strict FIFO (First-In, First-Out) rotations to prevent obsolete textbooks from being distributed. For educational publishers, managing book inventory demands robust logistics middleware similar to how manufacturing software tracks raw materials.

NCERT operated several regional warehouses with outdated barcode tracking processes. Operators carried paper checklists, and scans were logged manually into desktop terminals at the end of the shift. This manual method created massive backlogs, high picking error rates, and inventory discrepancies. While enterprise software systems like CRM development platforms and HRMS software manage customer relations and employee directories, warehouse management and real-time inventory management require specialized mobile client applications that sync with ERP backends.

To modernize their supply chain, they initiated a digital transformation program. They required custom ERP software development and mobile app development (including custom Android development and iOS development considerations) to power a mobile warehouse management system. By replacing manual audits with automated business automation, operators could run rugged handheld terminals to manage inbound receiving, label printing, grid slotting, and outbound picking.

2. Operational Challenges

Deploying a mobile tracking application inside massive national book warehouses introduced several challenges:

• Barcode Scanning Performance: Software camera-based scanning was slow and drained battery fast. The application needed to integrate directly with Zebra's physical laser scanners to handle high-frequency sweeps.
• Offline Resilience: Metal warehouse racks and concrete walls created Wi-Fi dead zones. The app had to operate offline, localizing scans and synchronizing data when re-connected.
• Misplaced Stock Prevention: Inbound books were regularly placed on the wrong shelves, making them impossible to find during picking. The app needed a validation loop that matched item scans against rack slot scans.
• FIFO Picking Accuracy: Operators picked the closest pallet rather than the oldest edition. The app had to enforce strict FIFO picking paths.

3. System Architecture & Mobile Engineering

Hedonist Solutions built a multi-platform mobile WMS communicating with a centralized database backend:

// Zebra DataWedge Android Intent Integrations

For the React Native application (Expo-based), native React development and Android development practices were crucial to bypass standard camera libraries. Instead of visual camera feeds, the system utilizes Zebra DataWedge to stream laser scan events directly. We configured a broadcast intent profile on the Android devices and registered a native intent listener inside the app's root lifecycle:

This configuration allows the application to capture raw barcode strings in less than 10 milliseconds, operating even when the screen is dimmed.

// Inbound & Outbound Verification Workflows

The inbound workflow contains three steps:

1. Setup: Scan the book SKU, verify details in the catalog (using the dynamic BookCreateForm if missing), and enter quantities.
2. Print: Compile parameters and transmit a ZPL label payload via TCP/IP sockets to the warehouse printer.
3. Verify: Label the pallet, place it in the target grid slot, and scan both the pallet label and the rack location label to lock the transaction.

The outbound workflow queries the backend database to extract picking queues based on FIFO rules. The mobile app directs the picker to specific rack coordinates (Aisle/Shelf/Bin) and forces a barcode scan of the bin location label to confirm picking from the correct lot.

// Local SQLite Caching & Offline Synchronization

We implemented offline storage helpers (AsyncStorage and local Room DB schemas) to buffer logs during Wi-Fi dropouts. This workflow automation manages transaction syncs without operator intervention. The app monitors network state; once connectivity is restored, the sync worker leverages secure API integration pathways to batch the offline payloads to the central FastAPI REST gateway and update the cloud applications database, resolving conflicts automatically.

4. Project Outcomes