IoT & AI Powered Property Management System Development Using .NET MAUI

We discuss how our engineering team developed cross-platform mobile applications for Android and iOS using .NET MAUI along with centralized desktop applications for monitoring and property management operations.

Incorporated solutions consisted of residential housing societies with ESP32-based sensors and AI Analytics for the management of visitors as well as smart surveillance and modern monitoring of smart apartments and housing societies

Client: Residential of 4500+ apartment units
Technologies: IP Camera, ESP32 Sensors, .NET MAUI Mobile App, AWS, AI Analytics

A large housing society apartment complex with 4500+ flats faced multiple operational challenges that affected both security and quality of life:

The security problems are:

• Improperly registered visitors - delivery people, salesman & unknown people
• Recording entries into the paper log by security was done incorrectly
• No check to see if there was an actual match between visitors and the account holder they were assigned to

The infrastructure problems include:

• The common area lights do not turn off and waste energy
• An overflow of the water tank went unnoticed until it started flooding into the common room
• Misunderstanding with the monthly bills for utilities between members because there is no meter for each unit separately.
• There is no early warning system for gas leaks or electrical issues.

Management Issues:

• Complaints were either verbal or submitted by typing with no way of knowing what was being responded to or how long it would take to resolve.
• Maintenance staff only worked in reaction to previous problems with no preventative maintenance.
• A lot of time was spent arguing each month at the meetings and most of it was based on unverified complaints.

The Committee for the Society decided to engage Adequate Infosoft to implement a complete smart solution.

Our company has developed and put in place a complete Property Management System (PMS) that uses both artificial intelligence (AI) and the internet of things (IoT) for security, energy, water, safety & maintenance.

This integration includes smart security, visitor management, energy monitoring, water management, safety alerts, maintenance tracking, advanced analytics using AI and a single point of monitoring through mobile and desktop applications built using .NET MAUI.

Module 1: Smart Access Control

Implementation:

Gate Camera:

AI-powered ANPR (Automatic Number Plate Recognition) for resident vehicles

Visitor Management:

QR code generated by resident, scanned at gate, photo captured

Biometric Integration:

Optional fingerprint for high-security areas (basement, server room)

Mobile App Approval:

Resident receives push notification for visitor, approves remotely

Results:

• All visitors are electronically logged, including date(s) of visit(s) and any photos taken.
• The number of unsuccessful entry attempts has been decreased by 95%.
• The amount of work performed by guards has decreased by 60% (as there are no longer manual registers).
• The average amount of time to access the building for delivery personnel is now only 15 seconds versus approximately 2 minutes prior to installation of this system.

Module 2: Energy Management

Implementation included the installation of motion sensors (using ESP32 microcontrollers) throughout stairwells, hallways/corridors, and parking areas, installation of smart relays to control lighting circuits, and development of a logic algorithm in which LED lights were dimmed to 20% during periods without motion; upon detection of motion, lights ramped up to 100%, and then returned to 20% after a period of 5 minutes without motion.

Results of energy efficiency measures included:

• 22% reduction in electrical consumption in common areas
• Projected annual savings of $8,500
• There have been no reported complaints of being in dark areas since motion response times are <200ms.

Module 3: Water Management & Smart Metering

Implementation:

Flow sensors monitoring each flat's water line, ultrasonic sensors measuring the level of the overhead tanks, and a motor controller automatically turning on/off based on the tank level.

Results:

No more billing dispute, as each flat can access the app that provides the exact amount of water consumed. Zero overflows for the last 6 months (used to have 2-3/month). 30% reduction in pump running time due to properly scheduled operations.

Module 4: Safety Sensors

Implementation:

• Gas leak detectors (MQ-135) in each kitchen
• Smoke/fire detectors in common areas
• Temperature/humidity sensors in electrical rooms

Critical Incident:

A gas leak sensor also sent an alarm at 2:30am in an empty flat during testing. The main gas line was automatically shut and security was notified. The leak was due to a faulty stove regulator. Potential disaster averted.

Module 5: AI Surveillance

Implementation:

We upgraded 24 existing analog cameras to IP cameras and added AI analytics:

AI Capability	Application
Intrusion detection	Restricted areas (roof, electrical room, basement)
Crowd density tracking	Party hall, pool area, temple
Abandoned object detection	Suspicious packages in parking
Facial recognition	Known residents vs. unknown (privacy: opted-in only)
Vehicle counting	Peak hour traffic analysis for gate staffing

Feature	Description
Guest pass	Generate QR code for expected visitor
Visitor log	See who visited your flat and when
Utility dashboard	Real-time water + electricity consumption (flat + common area share)
Complaint tracking	Submit and track maintenance requests
Community notices	Push notifications for society announcements
Emergency alert	One-tap alert to security + neighbours

Device	Quantity
IP Cameras (upgraded)	24
Motion sensors (ESP32)	48
Smart lighting relays	32
Water flow sensors	250 (one per flat)
Tank level sensors	6
Gas leak detectors	250 (optional, resident-purchased)
IoT Gateway (Raspberry Pi + LoRa)	4

"I can see water levels, power consumption, visitor logs and complaint status on my phone from anywhere in the world. The gas leak detection alone was worth the whole project."

— Housing Society Chairman, Supertech

Parameter	Case Study 1	Case Study 2	Case Study 3
Client Type	Property Management	High-Security Warehouse	Housing Society
Primary Problem	False alarms + delayed alerts	Undetectable internal data theft	Fragmented operations
Key Technology	PIR + React Native + AWS	NVIDIA Jetson + YOLOv8 + MQTT	ESP32 + .NET MAUI + LoRa
AI Application	Pet/human classification	Protocol deviation detection	ANPR + facial recognition
Deployment Scale	500+ properties	32 cameras, 1 warehouse	250 flats, 300+ sensors
ROI Period	12 months	8 weeks	30 months

Thinking of building an AI powered IP Camera or Smart Surveillance System? Adequate Infosoft is providing free technical consultation on firmware development, PCB design, IoT integration, cloud connectivity, mobile apps and production-ready camera solutions.