Hamaid Alsubhi, Waste Advisory Consultant at WSP and Chartered Waste Manager, and Golnaz Arab, PhD, P. Eng., Associate Director, Head of Waste Management AESG, explore how smart waste systems are reshaping Saudi cities and accelerating the transition to a circular economy.
Cities today are expected to demonstrate sustainability, rather than simply declare it. This shift is especially evident in the waste management sector. Initially, the service was designed to remain unseen since it was considered unsightly.
However, it is presently expected to deliver measurable environmental, social, and economic outcomes. Clean streets alone are no longer sufficient; governments require verified diversion rates, investors expect credible ESG reporting, and communities demand quiet, reliable, and resilient waste systems in increasingly dense urban environments.
This article has three primary objectives. Foremost, it seeks to identify and categorise key smart waste technologies currently being deployed in urban environments.
Additionally, it examines how these technologies collectively support the transition from conventional waste collection toward circular material management systems.
Lastly, it evaluates the role of Saudi Arabia as a practical testbed for smart waste infrastructure within rapidly urbanising contexts.
Conceptual Framework for Smart Waste Systems
This article adopts a conceptual framework that groups smart waste systems into five interconnected layers, namely smart collection systems, smart treatment and recovery systems, digital governance and traceability systems, behavioural and incentive-based systems, and infrastructure-integrated systems, such as AWCS. A combination of these layers forms an integrated smart waste ecosystem.
This framework provides a structured lens that is discussed in the subsequent sections to determine whether each technology is analytically linked to circular economy performance and long-term urban sustainability.
From Waste Collection to Material Management
For decades, municipal waste systems followed a simple operational model: place bins, collect according to fixed schedules, and remove from public view. While this linear approach was suitable for smaller, less complex cities, it is no longer aligned with modern sustainability goals.
Contemporary waste management requires a shift from this linear model toward a circular economy framework in which materials are retained in productive use through reuse, repair, recycling, and improved design.
Smart waste management represents a key enabler of this transition, reframing waste as a measurable material stream that can be monitored, optimised, and aligned with circular economy principles. It seeks not only to move waste efficiently but also to understand it; its quantity, source, quality, and end of life outcomes.
This data-driven approach allows decision-makers to answer critical questions:
- How efficient are current collection operations?
- Which locations generate the most waste?
- How much material is genuinely diverted from landfills, and can this be validated?
Without such data, circular economy aspirations remain theoretical.
Smarter Collection: Transition From Fixed Routes to Real Demand
Collection remains the most visible and often the most expensive component of the municipal waste management. In the past traditional systems, trucks operate on fixed routes regardless of actual container fill levels. This results in unnecessary trips, avoidable emissions, increased fuel consumption, and higher operating costs.
Smart collection systems challenge this legacy model. IoT-enabled sensors continuously monitor container fill levels, usage patterns, and in some systems weight. When paired with dynamic routing software, operators can shift to demand-based collection, servicing only when required.
This approach delivers immediate, measurable benefits:
- Reduced vehicle kilometres and emissions.
- Lower noise and traffic impact.
- Improved service reliability.
- Fewer overflows and related complaints.
Importantly, operational efficiency is not the end goal; it is the foundation for cleaner material streams, improved segregation, and stronger downstream recovery.
AI Sorting: Improving Material Quality
Circular economy performance depends heavily on what happens after waste is collected. Traditional material recovery facilities rely on manual sorting supported by mechanical separation. While effective to a point, these approaches struggle with increasing waste complexity.
Artificial intelligence and computer vision technologies are transforming this landscape. AI-enabled sorting systems can identify materials on conveyor belts at high speeds and with high accuracy. This enhances the consistency of separating plastics, paper, metals, and composites materials and consequently improving the overall material quality.
In regions seeking to attract investment into recycling infrastructure and recycled-content manufacturing, the impact is substantial. Technology shift recycling from a cost-driven service to a value-generating activity, which align environmental and economic incentives. Therefore, adoption of technology is crucial in revolutionising the new circular economy.
Smart Material Recovery Facilities Beyond AI Sorting
In addition to individual AI-enabled sorting units, smart material recovery facilities (Smart MRFs) integrate robotics, optical sorting, automated quality control, and real-time performance monitoring into a single operational system.
These facilities use continuous data feedback to adjust sorting logic, detect contamination trends, and optimise recovery efficiency across multiple material streams.
Consequently, Smart MRFs stabilise the quality and consistency of recovered materials, which reduces volatility in secondary material markets and increases confidence among downstream manufacturers.
Digital Traceability: Turning Waste into Accountable Flows
High-quality sorting and efficient collection are insufficient without verifiable tracking. Effective circular economy systems depend on transparency and trust among regulators, investors, manufacturers, and the public.
Digital traceability tools, such as radio frequency identification (RFID) tags, quick response (QR) codes, and digital chain-of-custody platforms, allow waste streams to be tracked from source through collection, treatment, and recovery. This enhances governance and supports compliance with emerging circular economy policies.
In the Middle East, evidence from recent waste and circular economy initiatives shows that smart waste systems increasingly function not only as operational enhancements but also as governance tools.
Although North Africa and Middle East account for 6% of the waste generated, they are growing rapidly, which makes digital traceability necessary. When properly managed, they help bridge the gap between policy ambition and measurable outcomes.
Digital Waste Analytics and Decision Platforms
Smart waste systems increasingly relying on digital analytics platforms that aggregate data from sensors, collection vehicles, treatment facilities, and traceability tools into unified dashboards.
These platforms enable predictive analytics, performance benchmarking, and scenario modelling, which allow municipalities and operators to move from reactive management to proactive planning. In the context of circular economy, digital analytics support material flow analysis and help identify leakage points where value recovery is lost.
Behavioral and Incentive-Based Smart Waste Systems
Technology-enabled behavioral systems, such as pay-as-you-throw (PAYT), incentive-linked smart bins, and digital reward platforms address issues of waste generation at source. These systems link waste quantities or contamination levels to financial or non-financial incentives.
Therefore, from a circular economy perspective, behavioral systems extend smart waste management upstream, which shifts focus from downstream recovery to waste prevention and material efficiency.
Automated Waste Collection Systems (AWCS): Waste as Urban Utility Infrastructure
Some smart waste solutions enhance the efficacy of existing systems, while others redefine the infrastructure entirely. Automated waste collection systems (AWCS), for example, operate as a utility network.
Waste is deposited into sealed inlets, transported via pneumatic pipelines, and delivered to a central collection station, significantly reducing or even eliminating the need for conventional collection vehicles within a district.
These systems offer notable advantages in dense urban environments:
- Improved hygiene and aesthetics
- Reduced traffic and emissions
- Consistent, reliable collection independent of weather or congestion
- Support for multiple segregated streams (e.g., residual waste and recyclables)
- Continuous performance monitoring and data analytics
Saudi Arabia as a Living Testbed for Smart Waste
Saudi Arabia has already implemented advanced waste technologies in highly demanding settings. In Makkah, automated systems support waste management operations in and around Al Masjid Al Haram, where waste quantity can reach approximately 600 tonnes per day during peak periods. Maintaining cleanliness and operational continuity in such a sensitive, high-density environment requires robust and resilient systems.
Similarly, the King Abdullah Financial District (KAFD) in Riyadh employs AWCS solutions. These implementations show that such systems are mature, scalable, and capable of meeting stringent service, sustainability, and aesthetic requirements.
A study conducted in 2023 indicates that AWCS deployment in Makkah has been generally successful despite a few optimisation challenges. The facility has the capacity to process 270 tonnes of solid waste per day captures the layout of the facility. Notably, it is the largest automatic waste collection system in the world according to MariMatic.
Saudi Arabia’s giga projects function as living laboratories, integrating waste infrastructure during early master planning rather than retrofitting it later. For rapidly growing global cities, the lesson is clear: early decisions on waste infrastructure shape urban outcomes for decades.
Limitations, Barriers, and Risks of Smart Waste Systems
Despite their potential, smart waste systems face several limitations and implementation challenges. High capital costs of the infrastructure-intensive solutions, such as AWCS, can restrict adoption. In addition, technical risks include sensor failure, data integration challenges, and cybersecurity vulnerabilities.
Furthermore, operational barriers may arise from skills gap, maintenance requirements, and resistance to organisational change. Addressing these challenges is essential to ensure that smart waste systems deliver long-term value rather than short-term innovation.
Conclusion: The Pursuit of an Integrated System
This article advances the smart waste discourse by framing technology as an integrated system that links infrastructure, operations, governance, and behavior. By applying this systems perspective to the Saudi Arabian context, the article demonstrates how smart waste can function as strategic urban infrastructure.
The findings suggest that cities seeking to advance circular economy outcomes should prioritise integration, early-stage planning, and data governance alongside technological adoption. Future research should focus on comparative performance data, lifecycle cost analysis, and the socio-economic impacts of smart waste systems across different urban contexts.
