LAMS Overview

Prototype dossier — Smart India Hackathon 2026

LAMS

Real-Time National Land Acquisition & Management System

One parcel of land, followed from proposal to possession — on a single map, in real time, whichever order each state already does its own paperwork in.

48PRD sections analyzed
15lifecycle stages, proposal to closure
9platform modules, one monolith
17technologies in the stack
Live parcel tracker Synthetic demo data
DEMO-UP-GZB-000123
Khasra no.142/2
JurisdictionGhaziabad, Uttar Pradesh
Coordinates28.6690° N, 77.4539° E
Acquisition status Identified

Cycling the parcel lifecycle from PRD §13.3 — this is what one `LandParcel` record lives through.

Scroll to unfold the system, or jump a section on the left

Sheet 01 / 16 — Why the platform is needed

The process today has no shared system of record

Land acquisition is state-executed and centrally guided, so every state built its own tools, at its own pace, in its own format. A file moves through thirteen conceptual steps between a District Collector's desk and the State Revenue Department — on paper, at every step. Select a stage below; the ones marked in red are named directly in the PRD's bottleneck analysis (§4).

Click a stage for what specifically breaks down there.

01Need identified
02 · bottleneckPhysical file prepared
03Manual submission
04 · bottleneckDistrict verification
05 · bottleneckState Dept. processing
06 · bottleneckPreliminary notification
07Objection hearing
08Final notification
09 · bottleneckAward declared
10 · bottleneckCompensation disbursed
11 · bottleneckR&R assessed
12 · bottleneckPossession taken
13Handover
Process step
Named bottleneck (PRD §4)

Select any stage above — the eight flagged in red are where the PRD's bottleneck table places the specific breakdown.

Sheet 02 / 16 — The TO-BE solution lifecycle

End-to-end digitized solution workflow

LAMS replaces paper file movement with a parcel-linked workflow engine, live compensation ledger, R&R tracking, and continuous AI delay-risk evaluation (PRD §5 & §10).

Click any stage to view input/output artifacts, actors, SLAs, and failure criteria.

01 · StartProject Proposal
02Digital Scrutiny
03GIS Parcel Tagging
04Approval Engine
05Prelim Notification
06Objection Window
07Final Notification
08Award Declaration
09Compensation Assess
10Disbursement Ledger
11Family Registration
12R&R Package
13Parcel Possession
14Project Handover
15 · ContinuousAI Delay Scoring
Process step
Verified Key Milestone
AI Risk Monitoring Layer

Select any solution stage above to inspect its data inputs, outputs, SLAs, and statutory failure conditions.

Sheet 03 / 16 — System Architecture & Component Interconnect

Modular Monolith with Dedicated GIS & AI Services

LAMS runs as a clean FastAPI modular monolith with PostGIS as the single unified source of spatial and relational truth, supported by GeoServer tile serving and XGBoost ML background inference (PRD §25 & §46).

Select architecture components to inspect service responsibility and protocol interactions.

Client TierNext.js Web & Mobile PWA
Edge GatewayAPI Gateway / CDN
SecurityKeycloak Auth (OIDC)
Core EngineFastAPI Monolith
EngineWorkflow Engine
DatabasePostgreSQL + PostGIS
CacheRedis In-Memory Cache
GIS ServerGeoServer (WMS/MVT)
Async QueueRabbitMQ / Celery
AI MicroserviceXGBoost ML Predictor
StorageMinIO / S3 Object Store
NotificationsNotification Worker
IntegrationIntegration Gateway
External SystemsGovt APIs (Mocked/Real)

Select any architecture node above to inspect its design rationale and operational responsibility.

Component Interconnect & Data Flow Traces

Select a real-world scenario to trace data movement across Frontend, Backend, Database, GIS, and ML services:

Sheet 04 / 16 — GIS & Spatial Architecture

The Parcel Geometry is the Anchor for Every Module

GIS is not a decorative map widget in LAMS. Every financial record, family entitlement, and possession panchnama attaches to a verified `LandParcel` spatial polygon in PostGIS (PRD §12).

PostGIS + Geometry

Spatial Storage

Stored as GEOMETRY(Polygon, 4326) with GiST spatial indexing. Supports spatial operations like ST_Within, ST_Intersects, and ST_Buffer.

GeoServer Vector Tiles

High-Performance Serving

GeoServer serves Vector Tiles (MVT) and WMS layers for snappy client rendering even with millions of parcel polygons nationally.

MapLibre GL JS

Open-Source Map Client

Client-side vector map rendering with zero proprietary API key vendor lock-in. Directly renders state/district boundaries and parcel overlays.

Interactive GIS Layer Visualizer Simulation

Toggle spatial layers below to simulate how the LAMS Map view dynamically overlays project alignments, cadastral polygons, and status flags:

Sheet 05 / 16 — Relational & Spatial Data Model

17 Core Entities Ensuring End-to-End Auditability

LAMS links project proposals directly to physical land geometry, multi-owner equity shares, financial disbursements, social impact family records, and system-wide audit logs (PRD §13).

Core Entity

LAND_PARCEL

ULPIN, survey/khasra no., geometry, declared vs computed area, acquisition_status.

Financial Entity

COMPENSATION

Owner ID, parcel ID, amount_assessed, amount_approved, amount_disbursed, status.

Social Impact

DISPLACED_FAMILY

Family head, household size, category, linked RRPackage, relocation status.

Audit Entity

AUDIT_LOG

Actor ID, action, entity, before/after JSON payload, timestamp, IP address.

Parcel Lifecycle State Machine

Every parcel transitions strictly through these legal states. Every transition generates an immutable `AuditLog` entry:

01Identified
02Proposed
03Under Scrutiny
04Verified (GIS)
05Notified (Prelim)
06Objection Period
07Notified (Final)
08Awarded
09Assessed
10Disbursed
11Possessed
12Closed

Sheet 06 / 16 — Config-Driven Workflow Core

State Approval Processes as Data, Not Code Changes

State-specific land acquisition laws are accommodated by defining approval chains, SLAs, and escalation logic inside JSON data templates — zero core code edits needed to onboard a state (PRD §14).

Sheet 07 / 16 — Core Functional Engines

Six Specialized Platform Engines

Every phase of the RFCTLARR 2013 lifecycle is powered by a dedicated domain module inside the modular monolith (PRD §11 & §15-18).

Module 01

Proposal & Scrutiny Engine

Digitizes proposal filing by Requiring Bodies, enforces mandatory survey documents, and provides revenue officer defect resolution toolkits.

Module 02

3-Tier Compensation Ledger

Tracks compensation through Assessed → Approved → Disbursed per owner/parcel. Explicitly surfaces unpaid compensation backlogs.

Module 03

R&R Entitlement Engine

Separates economically affected families from physically displaced families. Tracks housing, land-for-land, and annuity package completion.

Module 04

Parcel Possession Manager

Records possession parcel-by-parcel with mandatory geo-tagged photo panchnama evidence attachments. Derived project possession %.

Module 05

Document Vault (SHA-256)

Version-controlled document repository with mandatory SHA-256 cryptographic checksums preventing unauthorized file tampering.

Module 06

Timeline & SLA Engine

Monitors legal statutory deadlines and automatically triggers notifications and escalations upon SLA breaches.

Sheet 08 / 16 — Role-Based Dashboards & MIS

Near-Real-Time Executive Visibility

4-level drill-down hierarchy: India (National) → State → District → Project → Parcel, powered by PostGIS materialized views (PRD §19 & §20).

Sheet 09 / 16 — AI Delay-Risk Early Warning System

XGBoost + SHAP Explainable Delay Prediction

Predicts project delays before milestones are missed using tabular feature inputs. Purely advisory — never changes legal approval status (PRD §21).

Interactive AI Delay-Risk Simulator

Adjust the project risk parameters below to calculate real-time delay probability and view SHAP explainability weights:

Predicted Delay Probability
72%
HIGH RISK

Estimated Completion Delay: +42 Days

Comp Backlog
+0.32
SLA Breaches
+0.22
R&R Pending
+0.15

Sheet 10 / 16 — Data Provenance & Honesty Framework

Full Transparency on Real vs. Synthetic Data

LAMS uses real open government datasets for administrative boundaries and DILRMP stats, while using synthetic data for personal parcel/compensation records with explicit audit tags (PRD §22).

Dataset Source Organization Format Public Availability Prototype Strategy
LGD Directory Ministry of Panchayati Raj CSV / Web Service Public Used directly (Real Data)
Admin Boundaries geoBoundaries / Survey of India GeoJSON / Shapefile Public Used directly (Real Data)
DILRMP Progress Dept of Land Resources CSV / Portal Stats Public Used directly for narrative context
Parcel Ownership (RoR) State Land Record Portals Restricted API Private PII Synthetic Data (labeled is_synthetic=true)
Compensation Ledgers State Treasury Systems Restricted Private Financial Synthetic Data (circle-rate derived)

Sheet 11 / 16 — Integration Gateway & Adapters

Adapter Pattern Isolates External Dependencies

The `IntegrationGateway` uses fixed interface contracts so core platform logic never calls external government portals directly. Production onboarding requires swapping mock adapters for live endpoints (PRD §24).

Land Records Adapter

Bhulekh / Bhoomi / Dharani

Fetches parcel survey records and RoR ownership shares via state API adapters.

GIS Geoportal Adapter

ISRO Bhuvan / SVAMITVA

Imports drone cadastral geometry, satellite basemaps, and administrative boundary overlays.

Treasury Adapter

PFMS State Treasury

Pushes approved compensation disbursement vouchers and returns bank payment settlement receipts.

Sheet 12 / 16 — Recommended Technology Stack

Production-Grade Open-Source Stack

Chosen for high developer velocity, zero vendor billings, native spatial GIS support, and explainable ML (PRD §26 & §28).

Frontend

Next.js + TypeScript

Fast SSR web app with Tailwind CSS styling.

Maps

MapLibre GL JS

Open-source client vector tile rendering.

Backend

FastAPI (Python)

Async high-performance REST API monolith.

Database

PostgreSQL + PostGIS

Unified relational & spatial spatial database.

GIS Engine

GeoServer

OGC compliant WMS/WFS/MVT tile server.

Workflow

Custom JSON Engine

Config-driven state approval execution.

Cache

Redis

Session store & materialized view caching.

AI/ML

XGBoost + SHAP

Tabular delay prediction & explainability.

Sheet 13 / 16 — Security Architecture & Scalability

Jurisdiction Scoping & High-Throughput Design

Security is enforced server-side via JWT jurisdiction claims (State/District ID embedded). Scale is achieved via PostGIS MVT tiles and Redis materialized view caching (PRD §29 & §31).

Security Architecture

Multi-Tenant Jurisdiction RBAC

Every API query checks JWT claims. A Ghaziabad district officer cannot access Lucknow parcel records even if API parameters are tampered with. TLS 1.2+ transit, AES-256 storage, and SHA-256 document checksums.

Scalability Strategy

National Scale Execution

Designed for 10,000+ concurrent projects and millions of parcels. Read replicas handle dashboard aggregation loads. GeoServer MVT vector tiles prevent server strain by rendering tiles on client GPUs.

Sheet 14 / 16 — Stakeholder Permission Matrix

12 Defined User Roles Across All Levels

Every administrative level has custom tailored dashboards and strict read/write boundaries (PRD §7 & §11.3).

Stakeholder Role Jurisdiction Scope Key Platform Actions Assigned Dashboard
Central MinistryNationalView national KPIs, approve inter-state corridor policiesNational Dashboard
State Revenue DeptState-scopedConfigure state workflow JSON, issue gazette notificationsState Dashboard
District LAO / CollectorDistrict-scopedScrutinize proposals, declare awards, issue possessionDistrict Dashboard
Land Requiring Body (NHAI)Project-scopedCreate project, submit land proposals, track turnaroundProject Dashboard
Field OfficerAssigned ParcelsMobile GPS parcel tagging, photo panchnama captureMobile PWA Interface
Finance OfficerState / DistrictApprove compensation payments, disburse funds via treasuryCompensation Module
R&R OfficerDistrict / ProjectRegister displaced families, assign R&R housing/annuitiesR&R Module

Sheet 15 / 16 — Implementation Roadmap

Phased Delivery Schedule

Structured from SIH Prototype MVP to Full Production Deployment (PRD §45).

Phase 0 - 5 (MVP Scope)

SIH Hackathon MVP

Auth + RBAC, Project creation, Configurable Workflow Engine, PostGIS GIS Parcel Tagging, 3-tier Compensation Ledger, R&R family tracking, Possession recording, and XGBoost AI Delay model.

Phase 6 - 7 (Phase 2)

State Pilot & OCR

Document OCR auto-form prefilling, SMS/Email SLA auto-escalation dispatch, Bhuvan live API connection, and Native Mobile App.

Phase 8 (Phase 3)

National Production

Full DILRMP ULPIN national integration, multi-region DR deployment, formal CERT-In security audit, and Citizen Transparency Portal.

Sheet 16 / 16 — SIH Live Presentation Walkthrough

12-Step Judge Presentation Script & Differentiators

Step-by-step demonstration flow proving complete end-to-end functionality during hackathon judging (PRD §41 & Competitive Advantage).

Step-by-Step Live Demo

The Presentation Path

  1. Login as State Revenue Officer → Create Highway Project
  2. Upload Land Proposal + mandatory survey docs
  3. Digital Scrutiny: reject once with deliberate defect to prove resubmission loop
  4. GIS Parcel Tagging: draw highway alignment & tag survey numbers
  5. Workflow approval: watch proposal advance through state JSON chain
  6. Issue Section 11 Preliminary Gazette Notification
  7. Declare Award & compute compensation solatium
  8. Compensation: move status Assessed → Approved → Disbursed
  9. Register Affected & Displaced Families + assign housing package
  10. Record Parcel Possession with geo-tagged panchnama evidence photo
  11. Switch to National Dashboard: show live roll-up without manual re-seed
  12. Open AI Delay-Risk Panel: demonstrate SHAP explanation on delayed project
SIH Differentiators

Why LAMS Wins

  • Parcel Digital Twin: Every dollar and family record is anchored to GIS geometry, answering "which exact parcel is delaying the project."
  • Config-Driven Workflows: Solves state legal fragmentation via JSON templates, not hardcoded state logic.
  • Integrated GIS: Spatial parcel tagging is a mandatory workflow gate with SLAs, not an afterthought map view.
  • Honest Data Story: Explicitly labels synthetic records (is_synthetic=true) for full credibility.
  • Explainable AI: Uses XGBoost + SHAP to advise decision makers *why* a project is at risk.