Vision is the most celebrated human sense. Eighty percent of the information humans receive is obtained through vision. Machines capable of capturing images are now ubiquitous, but until recently, they have been unable to recognize objects in the images they capture. In effect, machines have been blind. This paper explores the revolutionary new capability of a camera to recognize whether a human is present in an image and take detailed measurements of the person’s dimensions. It explains how the hardware and software of the camera work to provide this remarkable capability in just 200 milliseconds per image. To demonstrate these capabilities, a home security application has been built called Security with Visual Understanding (SVU). SVU is a hardware/software solution that detects a human and then performs biometric authentication by comparing the dimensions of the seen person against a database of known people. If the person is unrecognized, an alarm is sounded, and a picture of the intruder is sent via SMS text message to the home owner. Analysis is performed to measure the tolerance of the SVU algorithm for differentiating between two people based on their body dimensions. / text

The study has consisted of creating a place for snow storage with a connecting storm water facility. This is based on findings regarding concentrations of pollutants in Luleå's snow storages in combination with Luleå's standards for design of these storages. For Luleå Municipality, the stormwater issue is relevant as the number of floods will increase as Luleå expands. This results in a greater ratio of hard-made surfaces with increased surface runoff that create risks of flooding and property damage, something that will intensify even further with climate change. Besides this, the runoff concentration of pollutants that are transported out into recipients also increases. The study has been carried out in Luleå, via Luleå Municipality and LTU. The purpose of the study was to answer the following questions:"What concentrations of pollutants are found in Luleå's meltwater?", "What does Luleå' smanagement of snow storage look like, and why?", "Where can a snow storage be placed in Luleå to enable year-round recreation?” and "Which stormwater solution should be chosen to filter pollutants from this snow deposit?". This was answered via seven different means of gathering data: literature studies, field studies/observations, meetings/interviews & E-mail exchanges, selection of a stormwater facility, calculations, simulations, and conceptual design. Through these means, the study concluded that the concentrations of pollutants in meltwater are generally greater than in stormwater, that there are recommendations regarding the size, location and safety of Luleås snow storages, that any snow storage should preferably be located where motor traffic is not present and that its space should be usable year round with regard to recreation, and that a wetland is the most suitable facility for filtering the pollutants in the meltwater from this deposit. Overall, the results conveys that the spaces set aside for snow and meltwater treatment should enable year-round recreation, in addition to their technical functions. However, does the results show nothing in terms of management of extreme cases of rainfall nor any types flooding preventions relating to stormwater management. This paper does not provide any suggestions for a snow storage site nor a stormwater treatment facility for cities with a similar or different climate. The reason that onlyr ecreation and pollution treatment were considered is because these are the most relevant in this context, firstly since toxins are more prevalent in meltwater than in stormwater, and because recreation associated with snow is a given aspect of usage. Thus were a suitable frame of question and suitable means used to generate reasonable and acceptable results.