This paper uses the concepts of milk runs as well as bin packing in order to optimize collection and reduce cost. Using the concept of “milk run” and an approach of time minimization, we can optimize the number of trucks and other vehicles used for picking and transporting waste. The objective function involves cost of transportation and is linked to distance travelled to dispose wastes. The constraints are those of vehicle capacity. The profile of different types of trucks obtained from milk run is used to compute number of trucks as well as to allot them to different trips.
Energy harvesting has been the empowering innovation in the internet of things to power the wireless sensors envisioned to be deployed ubiquitously. In recent decades, there has been an increasing drift towards remote sensor systems from wired networks in commercial and industrial applications due to expensive cabling and their non-feasibility in remote locations. The challenge is to convert these remote sensor systems into self-powered wireless sensor networks using energy harvesters. A brief review of current trends in the applications of energy harvesting in remote sensor systems is discussed in this chapter. A generic architecture of the energy harvesters and their transduction mechanisms and the design methodology of energy harvesters is introduced. The existing business products and the potential prototypes of the energy harvesters with their application domains are reported.
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