Jeremy Morris and Robert "Dylan" Walker (Maryland) presented at the 2017 International Solid Waste Association (ISWA) World Congress and WASTECON 2017 conference in Baltimore, Maryland on Tuesday, September 26, 2017.

Their presentation was entitled "Using Machine Learning Algorithms to Predict Landfill Gas Potential." It examined the use of machine learning algorithms to build solutions for new and emerging problems in the waste management industry. Existing applications of machine learning in waste management include waste stream sorting, predicting future waste streams, predicting demographic shifts, and predicting equipment maintenance requirements.

Jeremy Morris has more than 18 years of professional and academic experience in the field of solid waste management, with particular expertise in issues relating to waste disposal by landfill. Since joining Geosyntec in 2001, he has provided lifecycle technical design and project management services during permitting and construction of new landfills and lateral or vertical landfill expansions at numerous sites around the country and internationally. His technical specialties include landfill closure and post-closure care, waste characterization, and leachate characterization and treatment. He also has experience with landfill gas management and utilization, feasibility analyses for landfill-based renewable energy technologies, and sustainable approaches to landfill development and long-term management and remediation of closed sites.

Dylan Walker is a data management and visualization professional with extensive experience in database management, geospatial data analysis, and application integration and automation, including the development of site conceptual models, online data access and visualization, animation, automation programs, web and mobile application development, and geospatial analysis. Dylan has more than seven years of GIS and database administration experience. His experience is supplemented by extensive field and management experience, including geotechnical readings, groundwater and soil sampling and reporting, landfill gas monitoring, staff management, equipment management, work plan development and reporting.

Abstract

Making accurate predictions from complex data can be an overwhelming task, but with widely available data and machine learning providing new and powerful analysis methods, accurate predictions are increasingly easy to make. Existing applications of machine learning in waste management include waste stream sorting, predicting future waste streams, predicting demographic shifts, and predicting equipment maintenance requirements.

Using machine learning algorithms and cloud-computing power, it is possible to build solutions for new and emerging problems in the waste management industry. For example, an online retailer's sales data can be used to predict the waste materials that will come to a facility in the near future or birth records may serve to predict future waste quantities. Using domain knowledge and machine learning, it is possible to reduce both operating costs (such as fuel) and data collection costs. This presentation will explore machine learning algorithms that can be used to find the most important features in making a prediction, potentially reducing the amount of data required to reach an accurate conclusion while also saving time and money. Furthermore, an example of using machine learning to predict how changes in landfill operations might affect long-term gas production, recovery rates and utilization potential will be presented.

By attending this presentation, participants will better be able to discuss how modern computing and data analysis techniques as they apply to waste management, specifically as it applies to reducing costs and improving landfill gas production and utilization potential. The presenter will also introduce machine learning and present example models for discussion.

The World Congress is the biggest annual event organized by the ISWA. In 2017, WASTECON co-located with ISWA's World Congress to offer two exciting international events in one location on September 25–27 2017, in Baltimore, Maryland.

ISWA World Congress & WASTECON 2017 provides opportunities to see what's new in collection, processing, marketing and management of compost, recyclables and solid waste. Thousands of industry professionals from throughout the world joined for technical sessions, facility tours, exhibits and networking opportunities. They explored a variety of new topics and expand knowledge of what's happening in solid waste management.

ISWA's vision is an Earth where no waste exists. Waste should be reused and reduced to a minimum, then collected, recycled and treated properly. Residual matter should be disposed of in a safely engineered way, ensuring a clean and healthy environment. All people on earth should have the right to enjoy an environment with clean air, water, seas and soils. To be able to achieve this, we need to work together.

More Information

Learn more at: ISWA World Congress & WASTECON 2017
Read about the presentation at: Jeremy Morris and Dylan Walker Presentation
For consultation regarding machine learning algorithms, contact Jeremy Morris at This email address is being protected from spambots. You need JavaScript enabled to view it. or Dylan Walker at This email address is being protected from spambots. You need JavaScript enabled to view it..
Learn more about Jeremy at: https://www.linkedin.com/in/jeremy-morris-28b649/
Learn more about Dylan at: https://www.linkedin.com/in/robert-walker-3404b2100/