Sustainability & Consumer behavior towards Sustainability in Norway and Sweden

AimSustainability has become an important factor to consider while buying goods and services. People are being more conscious toward environmental impacts of products and services. This attitude has motivated many businesses to develop their production in contact with sustainability. The aim of this paper is to investigate different consumer behaviors toward sustainability in general and in relation to vehicles in Norway and Sweden.ApproachThe project has been embarked by dividing it into two tasks.1. Analyzing past, present and future development, growth and importance of sustainability concept. Describe the role of Government authorities in Norway and Sweden to promote sustainable consumption.2. Investigating important factors of consumer behaviors which influence their buying decision toward sustainable products in general and in relation to sustainable vehicles. Highlight the role of vehicle manufacturing companies to promote sustainable consumption.MethodA research has been conducted in order to explore consumer behavior toward sustainability in Norway and Sweden. Research is based on Document study and primary research which include questionnaire survey with consumers and interviews with vehicle dealers. In addition an expert inquiry is conducted to light up consumer intensions in Norway and Sweden toward sustainability.ResultsThe result of investigation has been revealed in shape of analyses and conclusion at the end. A comparison has been made between primary research and secondary research and findings are overlapping. Sustainable vehicles are being more popular among consumers in Norway and Sweden. Consumption trends are changing over time and environmental friendly attitudes are more developing among Swedish consumers as compared to Norwegian.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.