Aquila.GeoHandels.F10 1.0.1

Aquila.GeoHandels — Location Intelligence Usage Guide

Author: Aswin Sadhasivam Company: Aquila Innovations License: MIT © Aquila Innovations

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Overview

Aquila.GeoHandels provides location intelligence utilities for .NET MAUI applications, including:

• Fake GPS detection heuristics
• Location reliability scoring
• Drift filtering
• Circular and polygon geofencing
• Radius validation

This document explains how developers can integrate the Location Intelligence Engine to detect spoofed or unreliable GPS data.

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Installation

Add the NuGet package:

dotnet add package Aquila.GeoHandels

Or via Visual Studio:

Manage NuGet Packages → Search → Aquila.GeoHandels

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Basic Integration

1️⃣ Import Namespaces

using Aquila.GeoHandels.Models;
using Aquila.GeoHandels.Services;
using Aquila.GeoHandels.LocationIntelligence.Engine;
using Aquila.GeoHandels.LocationIntelligence.Models;

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2️⃣ Initialize Services

readonly GeoLocationService geo = new();
readonly LocationIntelligenceEngine engine = new();

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3️⃣ Get Device Location

var mauiLocation = await geo.GetRawLocationAsync();

if (mauiLocation == null)
    return;

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4️⃣ Build Intelligence Sample

var sample = new LocationSample
{
    Latitude = mauiLocation.Latitude,
    Longitude = mauiLocation.Longitude,
    Accuracy = mauiLocation.Accuracy ?? 25,
    Speed = mauiLocation.Speed ?? 0,
    Timestamp = DateTime.UtcNow,
    IsMockProvider = MockLocationHelper.IsMock(mauiLocation)
};

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5️⃣ Process Reliability

var result = engine.Process(sample);

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6️⃣ Interpret Results

if (result.IsReliable)
{
    // Safe to use location
}
else
{
    // Request new fix / warn user
}

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Understanding Scores

Suspicion Score

Indicates likelihood of spoofing.

Score	Meaning
0	Normal GPS
1–40	Minor anomalies
41–79	Suspicious
80+	Likely spoofed

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Confidence Score

Trust level of location data.

Score	Meaning
70–100	Reliable
40–69	Moderate
0–39	Unreliable

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Expected Behaviour

Scenario	Suspicion	Confidence
Real GPS	0	High
Fake GPS Enabled	~80	Low
Poor Signal	Low	Medium
Stationary Device	0	High

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Platform Notes

Android

• Uses provider mock detection
• Detects Fake GPS apps

Windows / Desktop

• Mock detection unavailable
• Heuristic scoring only

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Recommended Usage Pattern

Acquire MAUI Location
        ↓
Build LocationSample
        ↓
Process via Engine
        ↓
Use result.IsReliable

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Best Practices

• Always use MAUI Location for detection
• Do not bypass scoring
• Combine with geofence checks
• Avoid blocking users on first failure
• Log anomalies for analytics

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Example UI Feedback

ResultLabel.Text =
    $"Confidence: {result.ConfidenceScore}\n" +
    $"Suspicion: {result.SuspicionScore}";

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License

MIT License © Aquila Innovations

Aquila.GeoHandels

Enterprise Geolocation & Geofencing Toolkit for .NET MAUI (.NET 9)

Aquila.GeoHandels is a lightweight, cross-platform geolocation and geofencing library designed for production-grade .NET MAUI applications.

It abstracts platform GPS access and provides validated location intelligence including:

• Radius validation
• Circular geofencing
• Polygon campus boundaries
• Distance calculations

The library is built to be:

• Dependency-injection friendly
• Multi-platform compatible
• Testable
• NuGet-ready
• Enterprise extensible

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📦 Target Platforms

• Android (Primary)
• Windows
• iOS (Extensible)
• MacCatalyst (Extensible)

Framework:

.NET 9
.NET MAUI

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🚀 Features

Location Services

• Unified GPS abstraction
• Async location retrieval
• Accuracy-aware coordinates
• Timestamped readings

Distance & Validation

• Haversine-based distance calculation
• Radius validation
• Meter-level precision

Geofencing

Circular Fence

• Office radius validation
• Attendance tracking
• Check-in enforcement

Polygon Fence

• Campus boundaries
• Warehouse zones
• Multi-point areas

Architecture Benefits

• Interface driven
• Clean separation of concerns
• Replaceable platform providers
• Mockable for testing

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🧩 Installation

Local Project Reference

Add reference:

Right Click Solution
→ Add → Project Reference
→ Aquila.GeoHandels

NuGet (Future)

Install-Package Aquila.GeoHandels

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🧭 Quick Start

Using Services

using Aquila.GeoHandels.Models;
using Aquila.GeoHandels.Services;

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Get Current Location

var geo = new GeoLocationService();
var location = await geo.GetCurrentAsync();

Console.WriteLine(location.Latitude);
Console.WriteLine(location.Longitude);

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Radius Validation

var radius = new RadiusValidator();

var center = new GeoCoordinate(11.22711, 76.89497);
var staff = new GeoCoordinate(11.22720, 76.89510);

bool valid = radius.IsWithinRadius(
    staff,
    center,
    200);

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Circular Geofence

var circular = new CircularGeofenceService(radius);

bool inside = circular.IsInside(
    staff,
    center,
    200);

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Polygon Geofence

var polygon = new PolygonGeofenceService();

var boundary = new List<GeoCoordinate>
{
    new(11.1,76.8),
    new(11.2,76.9),
    new(11.3,76.7)
};

bool inside = polygon.IsInside(staff, boundary);

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🏗 Architecture Overview

Aquila.GeoHandels
│
├── Models
│   └── GeoCoordinate
│
├── Interfaces
│
├── Services
│
└── Platforms
    └── Android Provider

This layered structure ensures:

• Platform independence
• Testability
• Maintainability
• Extensibility

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🔍 Traditional Method vs Aquila.GeoHandels

Traditional Approach

Typical developer workflow:

• Directly call MAUI Geolocation API
• Write manual math
• Hardcode radius logic
• Duplicate code per project
• No abstraction
• No testing seams

Problems

• Tight platform coupling
• Repeated boilerplate
• Error-prone distance math
• Difficult maintenance
• No DI support
• Hard to scale

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Aquila.GeoHandels Approach

Abstraction

Platform GPS hidden behind interfaces

Reusable Algorithms

Validated distance engines included

Modular

Drop-in services

Clean Architecture

• Separation of concerns
• Clear contracts
• Easy mocking

Production Ready

• Structured for NuGet
• Multi-target build
• Maintainable codebase

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Comparison Table

Capability	Traditional	Aquila.GeoHandels
GPS Access	Manual	Abstracted
Distance Math	Custom	Built-in
Radius Validation	Custom	Built-in
Circular Fence	Manual	Built-in
Polygon Fence	Rarely done	Built-in
DI Support	No	Yes
Testability	Poor	Strong
Reuse	Low	High
Scalability	Limited	Enterprise Ready

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🧪 Recommended Use Cases

• Attendance apps
• Field workforce validation
• Delivery zone checking
• Campus access control
• Retail geo targeting
• Warehouse automation

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⚙ Best Practices

• Validate location accuracy before use
• Use ≥50m radius to avoid GPS drift
• Cache location reads
• Avoid rapid polling
• Log distance metrics
• Use polygon fences for large campuses

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🛣 Roadmap

• Background tracking
• Enter/Exit events
• Anti-spoof detection
• Google Maps overlay tools
• Fence persistence engine
• Location smoothing filters
• Geo analytics module

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👨‍💻 Author

Aquila Innovations

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📜 License

MIT (Recommended)