Project: Containers in a network

  • Duration: 01/2006 – 07/2007
  • Funding: Subsidie Electronische Communicatie of Senter Novum

About the project

In the Containers in a Network (CAN) project, Almende, Chess and Salland Electronics researched how sensors can be applied in bulk container management in a Klok Containers garbage processing plant. Self-learning ad-hoc communication networks predict when containers have to be emptied.

CAN proposed several new techniques to aid an operator at Klok Containers in container management. There are several garbage containers at Klok Containers that are each filled at different rates with different materials. The current, not so elaborate, way to know when a container has to be emptied, is by kicking to its exterior and inferring its fill grade by the sound.

The project’s solution exists out of sensor nodes that measure the amount of dirt in the containers, a wireless sensor network to store that information temporarily in a redundant distributed way, and a PC as network drain and graphical user interface to the Klok operator. The Klok operator receives a signal when a container is full, and he can subsequently inform the drivers of the shovels which container to empty.

Salland Electronics developed an ultrasonic sensor to measure the amount of dirt in the garbage containers at Klok Containers. In cooperation with other parties like the VU in Amsterdam, Chess developed a wireless network mote with an energy-saving information dissemination (gossip) protocol. Those motes are called MyriaNed nodes.

Our contribution

Almende developed higher level software on the nodes and on the operator’s computer. This level of software adapts to and learns from the environment and is implemented in an agent-oriented way. The system needs to be able to learn and adapt. In the first place, it has to relieve the system installer in fine tuning parameters at installation. Those are parameters like calibration levels when a container is full, and when it is empty. Its second purpose is to implement the forecasting functionality needed on an application level.

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