Enevo Waste Analytics Blog

February 26, 2016

5 tech solutions for preventing illegal dumping

5 tech solutions for preventing illegal dumping

As we reflect on 2015 and plan for 2016, many look to understand the pressures that affected their year.  While there were a wide variety of topics affecting the waste industry this year (see economics of recycling, ongoing commitments to CNG investments in the face of lower diesel rates, and exciting momentum toward reducing food waste), I wanted to write about a lesser publicized issue – illegal dumping.

As global cities prepare for higher urban populations, their classic public works infrastructure will inevitably be put to the test.  As a result, cities are employing a number of different strategies to try and get ahead of the social, economic, and environmental consequences of illegal dumping:

Los Angeles became publicly aware of their illegal dumping issues, and proposed a plan to develop a"cleanliness rating index" that will score the effectiveness of efforts to thwart illegal dumping down to the street level. Another item of the plan is to add 5,000 trash bins to the current 700 collected by the Public Works department.

The City of Baltimore is enhancing its residential waste collection containers. In November, the City Council approved a plan to purchase 210,000 garbage cans for just under $9M designed to reduce the costs of the city's rat eradication program, which saw a spike in calls due to increased illegal dumping. Their pilot of 11,000 containers reduced citizen calls for rat extermination by 26%. The containers also use RFID technology for asset management and collection detection.

Dallas is dealing with illegal dumping in more rural areas, which has led to them taking a different approach - the installation of motion activated cameras in strategic locations aimed to assist police in enforcing illegal dumping laws. The illegal dumping is indicative of a growing stray dog issue, which further highlights the need for comprehensive clean up efforts.

San Jose is turning to mobile technology to empower citizens to report illegal dumping, which comes along with stiffer penalties for those committing these crimes.

The challenge for cities dealing with illegal dumping is that it is extremely difficult to identify when it will happen, where it will happen, and how much will be dumped. Cities are looking to increase containerized infrastructure, as well as employ technology to help predict and therefore prevent waste in their public spaces. However, with already strained public works budgets, the true test of these solutions is whether the cities can achieve their desired results without drastically increasing their spending (how do you service more with the same resources - or fewer??).

These programs must increase services to areas of need, while at the same time reducing services to other areas in order to control their operating expenses. This requires a shift in mindset, as well as an increase in the collection and utilization of data, in order to embrace a dynamic service model aimed at efficiently shifting resources from low volume areas to high volume areas - and the understanding that those areas will change over time.

Globally, as well as here in the US (see City of Kirkland and Downtown DC BID) cities are beginning to use Enevo's sensor and predictive analytics technology to achieve this same goal. By deploying at an enterprise level, cities will be able to establish accurate baselines of their current state, and have a complete real-time view, which will allow them to employ various strategies in the most efficient manner. These can include targeting hot spots in real time, proactively visiting areas where there are recurring patterns of dumping, and maintaining the cleanliness of areas that only need minimal attention.

Monitoring city provided waste collection sites in order to deploy publicly funded resources in the most efficient manner is something that benefits all parties. As US cities continue to tackle the variety of urban challenges in 2016 and beyond, the emerging use of sensor technology and predictive analytics will play a key role in their success.

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