The overflowing garbage dumpsters are witnessed every day sitting partially covered behind a local grocer or fast food centre. They remind the amount of waste that is being generated by all the commercial businesses. Over the past several years, what you have not noticed probably is there is a very few less bulging dumpsters today as an innovative organization known as OnePlus Systems found a solution for this problem and transformed “garbage watching” into a high growth revenue stream that has lured businesses around the world including giants like Coca-Cola, Costco and HEB. The waste containers were made ‘smart’ starting with a fullness monitoring solution designed specifically for compactors.
Similar to any technology, considerable evolution had taken place in this field that started as a pressure sensor that is provided with an electronic device and designed to track the growing waste buildup in compactors. When the capacity reaches the optimal fullness, the sensors alert the operations automatically and clients call the waste disposal organization for removal before over-flow happens. They added a reporting functionality and web-based platform thereafter to start leveraging the waste data of their clients.
For non-compacting containers, analysis software, powerful routing and wireless ultrasonic fill-level sensors. Recently, the Metro series of sensors that use Sigfox, LoRa and Smart City IoT networks for communication are introduced. With the ultrasonic sensors based on IoT, one can witness the actual situation of waste containers in any area and plan the routes accordingly. Only 50 percent of the containers really need collecting per collecting cycle while the remaining are only half-full and can wait for the next collecting cycle.
Depending on the data received from ultrasonic sensors, the cloud system will generate smart collecting routes that can be sent to the truck drivers every morning. There is a provision for selecting the pick-up containers or the system can choose them for most optimized and efficient routes.
Smart fill-level sensors for any kind of containers
These sensors track the level of waste from every container and send it to cloud server wirelessly. The sensors are easy to install and compatible with all kinds of containers and are capable of tracking any garbage type.
User-friendly web-based visualization
The data gathered from the containers equipped with sensors is analyzed and processed by the cloud system. The data is then made available via a web-based platform. This system creates the most optimized and efficient collecting route for garbage trucks.
Increasing efficiency and reducing costs by 50 percent
The collection costs are reduced by almost 50 percent by driving in the optimized routes only. This kind of profit can be seen by eliminating pick-ups that are unnecessary. The costs for truck maintenance and servicing hours are reduced and environment can be protected in this process by creating less road wear and less CO2.
All these advanced devices for monitoring are aided by an equally sophisticated and innovative platform which arms client partners, private companies and municipalities with valuable visual tracking and real time reporting of their garbage and compactor receptacles including the optimized routing software so that the waste hauler can focus the resources only on containers that are full.
These solutions enable the organizations to re-allocate the operational time towards more mission critical initiatives. The waste monitoring solutions are being scaled to various sectors like collecting waste near the oil tankers.
Guest Author Bio:
Savaram Ravindra was born and raised in Hyderabad, popularly known as the ‘City of Pearls’. He is presently working as a Content Contributor at Tekslate.com. His previous professional experience includes Programmer Analyst at Cognizant Technology Solutions. He holds a Masters degree in Nanotechnology from VIT University. He enjoys spending time with his friends. He can be contacted at [email protected]. Connect with him also on LinkedIn and Twitter.