Systems and methods for detecting a waste receptacle, the system including a camera for capturing an image, a convolutional neural network, and processor. The convolutional neural network can be trained for identifying target waste receptacles. The processor can be mounted on the waste-collection vehicle and in communication with the camera and the convolutional neural network configured for using the convolutional neural network. The processor can be configured for using the convolutional neural network to generate an object candidate based on the image; using the convolutional neural network to determine whether the object candidate corresponds to a target waste receptacle; and selecting an action based on whether the object candidate is acceptable.

Recycling systems can include a conveyor system, an optical device, and a processor operable to detect, identify, and count redeemable objects. The conveyor system can include a plurality of bins and be configured to move the bins from a first end of the conveyor system to a second end of the conveyor system. The optical device can be situated and configured to capture an image of a plurality of objects within a bin of the conveyor system. A processor including computer-readable instructions can be configured to detect and identify the objects within an image captured by the optical device as belonging to one or more object classes. Each object class can determine whether an object is redeemable or unredeemable. The processor can be configured to provide a count of only those objects identified as redeemable.

One example embodiment is adapted for use in facilitating collection and transport of memory devices, e.g., drives, motherboards, etc., e.g., for the purposes of subsequent destruction. The example embodiment has an outer bin, also called a garage or outer enclosure, within which is placed an inner bin with wheels. Once closed and locked, the outer bin has a door that can be opened so drives or other memory devices can be inserted. The drives then fall into the inner bin and, once sufficiently filled, the inner bin be easily wheeled out from the outer bin. The inner bin has its own locking lid that is secured when transporting the inner bin with the drives, e.g., to a destruction facility or area. Other features are provided as described below. Enhanced synergistic security features include use of multi-point locking latches to secure doors and lids, metal construction of the bins, and so on. The bins are sized to facilitate efficient collection and transport of potentially sensitive data center media.

A refuse container having an indicator assembly for informing a waste generator of contamination in a waste stream. A refuse container includes a container body comprising a receptacle portion and a lid coupled with the receptacle portion. The receptacle portion includes a plurality of walls that together define an enclosed space for containing refuse. An indicator device is coupled with the container body. The indicator device is movable relative to the container body between a first position and a second position. First indicia is provided on one of the indicator device or the container body. When the indicator device is in the first position, the first indicia are visible from the exterior of the refuse container, and when the indicator device is in the second position, the first indicia are not visible from the exterior of the refuse container.

A method and device for positively identifying that a dump event of a refuse container has occurred into a refuse hopper of a refuse vehicle are provided. When used with route software, alerts may be generated if a specific refuse container is missed or if an unexpected dump event occurs during the route.

A recycling identification container, including a main body, including a first section to store at least one trash item therein, a second section connected to the first section to store at least one recycle item therein, and a divider disposed between at least a portion of the first section and the second section to separate the first section from the second section, a cover unit removably connected to at least a portion of a first end of the main body to cover an interior of the main body, and an identification scanner disposed on and within at least a portion of the main body to scan properties of at least one item based on a predetermined algorithm to determine whether the at least one item is at least one of the at least one recycle item and the at least one trash item.

Waste chute devices and methods for using the same are provided. In some embodiments, a method for operating waste chutes comprises: receiving, using a hardware processor of a waste chute device, an identity associated with a user of the waste chute device; in response to receiving the identity associated with the user, allowing, using the hardware processor, a door of the waste chute device to be opened; determining, using the hardware processor, a number of items and at least one type associated with the items that have been placed in an opening of the waste chute device; determining, using the hardware processor, that the door of the waste chute device has been closed; updating, using the hardware processor, information associated with the user based on the number of items and the at least one type of items that have been placed in the opening of the waste chute device; and providing, using the hardware processor, the user with the updated information.

A method for efficiently and automatically requesting waste collection services through the use of mobile communication devices is disclosed. The method utilizes a fill-level sensor or fill-level sensors attached to dumpsters of various sizes. The fill-level sensor is configured to monitor a dumpster's capacity in terms of waste volume. Whenever the volume reaches a predetermined fill-level set by the generator, an automatic collection request is sent out to at least one hauler capable of carrying out the collection.

A system includes a trash box, a data acquiring device, a computer of a facility, a mobile, and a management server. The trash box is placed in a space facing a road for the mobile in the facility. The data acquiring device acquires collection status data of a trash in the trash box. The management server or the computer of the facility determines whether a collection of the trash box is required based on comparing a judgment element calculated by using a collection status data with a judgment threshold. The management server transmits a collection order to the mobile if it is determined that the collection of trash box is required. The mobile comprises an automatic collection device. The automatic collection device performs an automated replenishment control of the trash box if the mobile receives the collection order.

Systems and methods for detecting a waste receptacle, the system including a camera for capturing an image, a convolutional neural network, and processor. The convolutional neural network can be trained for identifying target waste receptacles. The processor can be mounted on the waste-collection vehicle and in communication with the camera and the convolutional neural network configured for using the convolutional neural network. The processor can be configured for using the convolutional neural network to generate an object candidate based on the image; using the convolutional neural network to determine whether the object candidate corresponds to a target waste receptacle; and selecting an action based on whether the object candidate is acceptable.