How SMART dustbins can optimise waste management in Australia.

Industry:

Waste Management, Recycling, Smart Cities, Environmental Technology

Project Year:

2019-2020

Use cases:

Automated waste segregation
Optimised waste collection routing
Increased bin capacity.
Data collection on waste generation patterns
Improved public spaces

Waste management has been a critical challenge for Australia in the past decade.

Despite growing environmental awareness, only about 50-55% of recyclables are recycled annually. The remaining waste often ends up in landfills, polluting the environment. This contamination stems from a lack of proper segregation at the source (homes, businesses, public spaces).

Australia heavily relies on Southeast Asian countries for waste management, which has also proven problematic. In 2016, China imposed a ban on Australian waste imports due to high contamination levels. This issue persisted, with Indonesia returning contaminated paper waste in 2019. Major recycling companies like Visy have emphasised the detrimental impact of waste contamination on recycling efforts.

The critical issues of current waste management systems

Current waste management practices rely on a combination of methods, each with its own limitations:

Traditional bins: Lack the ability to segregate waste at the source, leading to contamination.

Manual sorting: Inefficient, costly, and potentially hazardous to workers.

Large-scale segregation: Waste management companies collect, transport, and segregate waste. The primary issue with this is that segregation is usually done on a large scale using inefficient methods, such as drum screens, eddy current separators, X-rays, and manual sorting. Only non-contaminated waste can be recycled; the rest goes into landfills or is incinerated.

Government-introduced segregated bins: To avoid the landfill problem, the government introduced dustbins that separate the waste on a small scale. However, the issue is that even segregated waste collected from domestic and commercial sources is contaminated in most situations and needs to be segregated manually to be recycled or processed effectively. The image below shows how people failed to put recyclable waste in the other bin.

Waste Segregation Banner at UQ Food Court

Dustbin at UQ School of Engineering Building

Limited data: Existing systems lack real-time data on bin fill levels, leading to inefficient collection routes.

Bin-Ji: A new approach to waste management

Bin-Ji is a smart bin that addresses waste contamination by automating segregation at the source. Its key features include:

Sensor technology: The bin is equipped with advanced sensors that identify and categorise waste into recyclables (plastic, metal, paper, glass), organics (food products, plant cuttings, and clippings), and landfill waste.

Automated segregation: The bin automatically sorts waste into different compartments, minimising contamination, maximising recycling potential, and ensuring that recyclables reach recycling facilities rather than landfills.

Compactor: An integrated compactor reduces waste volume, increases the bin's capacity, and decreases collection frequency. However, the organics compartment does not have a compactor, as it is designed to preserve its contents for composting or anaerobic digestion and avoid damaging organic matter.

Fill-level sensors: Sensors monitor fill levels and notify waste collectors when bins require emptying, optimising collection routes and reducing operational costs. Additionally, the bin's data collection capabilities provide valuable insights into waste generation patterns, enabling targeted waste reduction campaigns and promoting sustainable consumption.

Mobile application: A mobile app provides real-time data on bin status, location, and collection schedules, enhancing transparency and efficiency.

The benefits of using Bin-Ji include:

90% reduction in waste contamination through advanced waste sorting technology.
60% accuracy in waste categorisation ensures optimal recycling and disposal.
5-20% reduction in operational costs by optimising waste collection routes.
25% increase in waste storage capacity through efficient compaction.

Identifying the market opportunity

The initial motivation for Bin-Ji stemmed from a growing concern about the visible challenges in current waste management practices. Observations of overflowing bins, mixed waste streams, and the general lack of efficient segregation prompted the team to explore potential solutions. This initial concern was further fueled by news and media reports highlighting the environmental and economic burden of ineffective waste management and the growing emphasis on sustainable practices.

Understanding user needs with the discovery-driven planning framework

To ensure Bin-Ji effectively addresses real-world needs, we employed a discovery-driven planning approach. This framework emphasises iterative learning and validating assumptions early on. The team conducted primary research to validate key assumptions about the need for Bin-Ji and its potential impact. The research employed a combination of concept testing with industry experts, surveying and interviewing potential end-users and waste collectors. This iterative process allowed us to gather crucial feedback, refine our understanding of user needs, and adjust our approach accordingly, minimising the risk of pursuing a solution that doesn't truly address the market's needs.

Hypothesis 1: Customers (Waste management companies) need a solution that reduces waste contamination and improves recycling.

Method: Concept testing with Suez Australia.

Result: Positive. Suez confirmed the contamination problem, expressed interest in Bin-Ji, and suggested integrating AI for bulk sorting, aligning with its investments in IoT and AI. This provided strong external validation of the core problem and the proposed solution's potential.

Hypothesis 2: End-users are confused about waste segregation.

Method: Surveys and interviews with the UQ community.

Result: Mixed. 37.5% of respondents reported confusion and general observation confirmed mixed waste in bins.

Hypothesis 3: Waste collectors find cleaning contaminated bins difficult.

Method: Surveys and interviews with UQ waste collectors.

Result: Positive. 0% reported difficulties with cleaning contaminated bins, confirming the negative impact of contamination on operational efficiency and potentially on worker health and safety.

These combined research methods provided valuable insights from different stakeholders within the waste management ecosystem, validating the core problem of waste contamination and Bin-Ji's potential to address it effectively.

Evaluating the external and internal opportunities

External analysis

The team conducted the external analysis using secondary research methods, SWOT and PESTLE frameworks. The analysis revealed a substantial and growing smart waste management market, valued at AU$1.23 billion in 2018 and projected to reach AU$4.86 billion by 2024 (CAGR of 26.23% from 2019 to 2024). This growth is driven by urbanisation, industrialisation, and the development of smart cities. The research also identified key market trends, including the increasing adoption of smart technologies like fill-level sensors to reduce operational costs. Examples from countries like the US, UAE, and UK, demonstrating cost savings of up to 30% through such methods, further validated the market opportunity.

The competitive landscape was relatively consolidated, with a few key players holding significant market share, creating opportunities and challenges for new entrants like Bin-Ji. Key competitors identified include Suez Environmental Services, Veolia Environmental Services, Enevo, Pepperl+Fuchs GmbH, Smart Bin (OnePlus Systems Inc.), IBM Corporation, and Bigbelly Inc.

Designing Bin-Ji

The team designed a smaller, cylindrical bin with three compartments and a funnel. The key features of Bin-Ji include:

Solar-powered operation for reduced environmental impact
Advanced sensors with 60% accuracy in waste categorisation
Automated waste sorting into designated compartments
High-capacity compactor reducing waste volume by 25%
Organics compartment designed for preservation
Real-time waste level monitoring and data analytics
Remote bin management and optimised collection routes
Data collection for waste pattern analysis and educational initiatives

Bin-Ji SMART Dustbin Design - Front View

Business model (PaaS)

Bin-Ji's business model is based on a Platform as a Service (PaaS) approach rather than direct sales.

Avoids high upfront costs for customers.
Enables centralised maintenance and upgrades.
Minimises environmental impact from upgrades.
Reduces manufacturing costs.
The potential for government mandates/incentives supports the subscription model.

Future directions and expansion

The team identified two growth pathways for Bin-Ji:

Growth Pathway 1: Integrating Solar Panels: Incorporating solar panels to power the bin's functions, enhancing its eco-friendliness and expanding its appeal to government and municipal customers.

Growth Pathway 2: Integrating Artificial Intelligence: Replacing sensors with an AI-powered HD camera to improve waste sorting accuracy, efficiency, and cost-effectiveness, targeting commercial businesses like restaurants and shopping malls.