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Managing resources effectively is crucial for sustainable development. Our IoT solutions provide real-time insights to tackle water management, waste monitoring and pollutions control.

Driving Sustainability

with

Intelligent

IoT Solutions

IoT use cases

Real-World Impact:

Sustainability

IoT Use Cases

Explore how organizations are already transforming urban living using our solutions.

Real-World Impact:

Sustainability

Accelerating Decarbonisation with

Data-Driven Insights

Accelerating Decarbonisation with

Data-Driven Insights

Today’s buildings must do more than stand they must think, sense, and respond.

Sustainability isn’t achieved in spreadsheets—it demands live, verifiable data and automated action across every resource stream.

Our sustainability-focused IoT fabric transforms scattered meters and manual logs into a single, intelligent nervous system that:

  • Captures second-by-second readings from energy, water, and waste sensors across multiple facilities, surfacing inefficiencies that monthly bills can never reveal.

  • Correlates renewable generation, grid carbon intensity, tariff windows, and local weather so operations run when power is cheapest and cleanest.

  • Detects micro-leaks, equipment drift, and abnormal chemical usage in real time, triggering alerts before minor issues become regulatory violations.

  • Feeds scope 1–3 emissions, water footprints, and landfill diversion rates directly into ESG dashboards, slashing manual reporting by countless staff-hours each quarter.

With every kilowatt, litre, and kilogram tracked and optimised, organisations move from pledging net-zero to proving progress—while simultaneously cutting costs and risk.

Real-time IoT dashboard showing live metrics from connected smart devices.

Urban areas struggle with chronic congestion, high-energy street lighting, and declining air quality. IoT Shabaka deploys an integrated sensor-to-cloud architecture that synchronises traffic signals, dims or brightens LEDs in real time, and streams hyper-local environmental metrics. The platform ingests multi-source data, applies AI analytics, and issues automated control commands, creating a self-optimising urban fabric.

Solution Overview

Core Architecture & Components

Layer
Key Elements
Functionality
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Impact Area
Metric
Global Benchmarks
O&M cost
▼ 40 % lighting maintenance via predictive alerts (Barcelona pilot)
Automated fault detection planned under TASMU Transport use-cases
Emissions
▼ 10-12 % CO₂ from reduced idling (Singapore GLIDE analysis)
Projected 5 % GDP-linked gain from smart-city efficiencies by 2022
Energy use
▼ 30 % lighting power cut after LED+IoT rollout (Barcelona)
Msheireb Downtown reports 30 % lower overall energy demand via 8 000 smart meters
Traffic flow
▲ 15-25 % faster average corridor speed (AI-signal coordination, Singapore)
ITS roadmap targets 20 % reduction in delays on Doha arterials (Ashghal)

Quantified Benefits

Strategic Adoption Roadmap

Deployment under this framework positions municipalities to exceed Qatar National Vision 2030 sustainability and mobility targets while delivering measurable economic return.

Align with National Platforms

Adopt Open Standards

Deploy ITS devices certified under Ashghal V&V guidelines to ensure interoperability and lifecycle security.

Prioritise high-congestion corridors for adaptive signal control, followed by district-wide smart lighting retrofits linked to demand-based dimming profiles.

Phased Roll-out

Enforce Qatar Cybersecurity Framework controls on all IoT endpoints; anonymise mobility data in accordance with Law (13) of 2016 on Personal Data Protection.

Data Governance

Structure energy-service agreements (ESPCs) that guarantee ≥25 % energy savings, financing CAPEX through realised utility reductions.

Performance Contracts

Integrate datasets through MCIT’s TASMU Smart Qatar backbone to leverage existing sector APIs and comply with ISO 37122 smart-city KPIs.

Smart IoT sensors monitoring air, traffic, and utilities in Qatar city.

Your

IoT Transformation

Roadmap

Smart factory in Qatar using IoT sensors for predictive maintenance.
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