Waste management is a critical issue facing businesses around the world. As companies grow and consumption rises, the amount of waste generated continues to increase. At the same time, there is mounting pressure on businesses and municipalities to divert more waste away from landfills towards sustainable outcomes like recycling and reuse.
Managing waste across multiple business locations can be even more challenging. Companies must navigate varying regulations and infrastructure while meeting sustainability goals and controlling costs. A flexible approach adaptable to local contexts is key. Companies can make progress by partnering with businesses that have a national footprint to assess needs, implement customized site-level plans, and identify opportunities for improvement through data analysis. Small changes make a collective impact while benefiting the bottom line.
Achieving higher recycling rates is no easy feat. It requires extensive coordination among waste generators, haulers, sorting facilities, and end markets. However, emerging artificial intelligence (AI) solutions are proving to be a game-changer in optimizing waste diversion. AI-powered software can help select the ideal recycling facilities, determine the best transport routes, and provide actionable insights to boost recycling performance.
The Power of Data
At the heart of effectively applying AI to waste management is comprehensive data, especially around matching the excess materials with the best end-of-life facility. Detailed datasets on material types, exact composition percentages, volumes generated, and viable destinations based on quantity and quality requirements enable intelligent recommendations optimized for reuse, repurposing, and recycling.
Textiles exemplify these data challenges. Solutions exist for recycling 100% cotton or polyester fabrics but become far less common as materials blend, requiring AI to match material attributes to qualified destinations. Aggregating sufficient volumes to justify transportation also poses difficulties.
For example, CheckSammy, a Dallas sustainability and waste operator, has a network of over 25,000 reuse and recycling facilities. CheckSammy's upcoming sustainability-focused AI, named Sammy, will leverage this rich data set to optimize where collected textiles should be routed to maximize landfill diversion in a cost-effective manner while minimizing distance traveled. Whether the material is in a single location, or spread across dozens or even hundreds of facilities nationwide, plays a big role in determining the optimal processes.
In addition, by tracking the material life cycle via chain-of-custody data from initial collection through final processing, transparency and responsible handling are assured and validated. Both the breadth and depth of datasets, especially around end-of-life pathways, empower AI tools to drive innovation in waste reduction.
AI-Based Facility Matching
Matching the right waste materials to the right recycling facilities is a complex process. It requires assessing multiple factors, including technical compatibility between material and facility, available processing capacity, distance, costs, logistics, and market demand for the recycled output.
The Sammy AI engine can rapidly analyze and synthesize all these variables to determine the optimal destination facilities from among thousands of options in their networks. This automated matching enables more waste materials to be matched to appropriate recycling facilities, leading to higher landfill diversion rates, greater monetization of the material, and larger volumes being sustainably processed.
Route Optimization
Transporting waste and recyclables efficiently is vital for cost management, safety, and sustainability. AI-powered route optimization considers truck availability, waste volumes, consolidation opportunities, facility schedules, road networks, and real-time traffic to plan the best routes. This minimizes mileage and Scope 3 emissions from collection and transport.
Dynamic route optimization also facilitates combining material batches heading to common destinations, which allows carriers to maximize payload on return trips too. By coordinating transport for both waste removal and recycling, AI systems enhance efficiency, economics, and environmental performance.
Ongoing Performance Tracking
Rather than just a one-time planning tool, AI plays a critical role in providing ongoing visibility into waste and recycling programs. CheckSammy offers this capability through its proprietary Veridiant platform, which tracks key metrics, including waste generation, contamination, diversion rates, participation, costs, and revenues. As an integral part of CheckSammy's service, Veridiant enables the ongoing optimization and analytics critical to effective waste management programs.
With regular data-driven insights on performance against sustainability targets, CheckSammy customers can pinpoint improvement opportunities, address problems areas, and realize program goals through AI-powered continuous improvement. The waste and recycling landscape evolves constantly, and the integrated visibility Veridiant provides allows for adaptation in real-time.
Granular data and dashboards give managers insight to refine processes and infrastructure continually. AI aids further by detecting anomalies, diagnosing problems, and prescribing corrective actions to boost recycling results. This leads to data-driven decision-making for continuous improvement.
The Human Touch
AI augments but does not replace human oversight in sustainable waste management. While AI recommendations from Sammy provide impartial, high-quality guidance grounded in facts, data, and logic, human judgment is still essential to make final decisions, factoring in experiential knowledge and long-term strategic priorities.
The combination of human values with Sammy's data accelerates progress in fostering circular economies where waste is eliminated through data-optimized design, detailed analytics and complete recovery and monetization of excess materials.
Looking Ahead
As CheckSammy's Co-founder and CEO Sam Scoten summarized, "Our goal is driving innovations that push the envelope in reducing waste expenses while achieving sustainability targets. Working closely with our customers, we provide both cutting-edge AI tools as well as personalized, expert support to transition from waste liabilities to waste assets. Together, we can divert millions more pounds from landfills to feed critical recycling supply chains. AI is also a major tool we're leveraging to expand globally, allowing us to rapidly expand our facilities network within target countries."
The waste challenge grows increasingly complex with shifting consumer behaviors, products, packaging and stakeholder expectations. Yet an AI like Sammy promises practical solutions to tangibly improve results through optimized routes and aggregate pricing to reduce disposal costs. Comprehensive data tracking also measures diversion rates, emissions, and participation to demonstrate sustainability progress.
Even as the landscape evolves, AI equips businesses and municipalities to continuously tailor waste programs, enhance responsiveness, and achieve higher diversion rates cost-effectively. Beyond lofty goals, AI delivers actionable insights to meet urgent real-world waste targets. AI enables measurable improvements in waste disposal expenditures, tracking, and landfill diversion.
More importantly, AI streamlines and accelerates a company's path towards diverting their excess materials away from landfill, and leverages AI's capabilities to find the most efficient, affordable and sustainable solution, making AI a truly revolutionary and practical tool in evolving a company's waste removal efforts.
