A cabling system and accessory for attachment to the rubber boot surrounding the metal chute area of either a front or rear loader concrete truck for improving and enhancing the function and purpose of the rubber boot and chute area of a ready mix concrete truck, and for increasing the safety, health, and environmental aspects of cleaning thereof, wherein physical exertion and risk of injury to the truck operator is minimized, wherein the quantity of water utilized for cleaning is reduced, wherein the overall cleanliness of the truck is improved, and wherein the functional life span of the boot, chute, mechanical parts, and the truck itself is increased.

Disclosed are method and system for treating concrete in mixing drums of delivery vehicles having automated rheology (e.g., slump) monitoring systems programmed to dose fluids into concrete based on the monitored rheology. The present invention takes into account a Revolution-To-Discharge value (RTD) which reflects drum rotations needed to move concrete towards and through the mixing drum opening from which concrete is discharged, and also takes into consideration a Volume-Per-Revolution-Upon-Discharge (VPRUD) value which reflects the relation between the rate of discharge and rheology (e.g., slump) of concrete upon discharge. The invention is especially useful for reclaiming concrete in the drum after delivery and can confirm rheology based upon peak (maximum) discharge pressure. The present inventors found surprisingly that discharge pressure readings are useful for recalibrating automated rheology monitoring systems as well as for reporting and/or treating the remainder concrete.

This specification relates to systems (100), methods and apparatus for intelligently controlling the drum rotation of a concrete mixer (104). According to a first aspect of this specification, there is described a method for controlling a concrete mixing drum (104) on a concrete mixer vehicle (102), the method comprising, for each of a plurality of time-steps: inputting, into one or more machine-learned models (210), input data comprising a current state of the concrete mixer vehicle and one or more delivery requirements for a concrete mix in the concrete mixing drum; processing, using the one or more machine-learned models, the input data to generate a drum rotation cycle data (c) for the concrete mixing drum; outputting, from the one or more machine-learned models, the drum rotation cycle data; and controlling the concrete mixing drum based on the generated drum rotation cycle data.