Browsing by Subject "Kysely"

Municipal environmental authorities are required to conduct environmental monitoring. Unmanned aerial vehicles, UAVs, may be helpful in environmental monitoring but their applicability as a tool for municipal environmental monitoring has not been studied. In this thesis it was studied, how municipalities have been utilizing UAVs. Additionally, UAVs applicability for environmental monitoring and inspection work was tested using a litter monitoring experiment as an example. In the first part of the study, a questionnaire was sent to municipal environmental authorities in Finland, to municipalities in Sweden and to those participating in Eurocities WG Waste group (n = 512), covering the used applications, their utilization frequencies and successfulness, reasons for failures and future plans. The results were analyzed using descriptive statistics. In the second part of the study, a UAV was utilized in a litter monitoring experiment on four sites in Helsinki. Litter by category and leaves were counted based on visual observations from UAV imagery. The accuracy of UAV imagery detection was assessed by comparing its and ground assessment (GA) results. On one site, a control group also carried out UAV imagery detections in order to assess the magnitude of bias or offset occurring when both the GA and the litter detection from UAV imagery are conducted by a single individual. The Wilcoxon signed rank and Cronbach’s α reliability tests were used for statistical analysis of the results. Response rate of the questionnaire was low, 3.7% (n = 19). The pool of used applications was extensive and covered a variety of monitoring and inspecting targets with emphasis on the presumably manually piloted applications. Utilization was very successful. The most important reasons for failures were poor weather followed by lack of information and expertise. UAVs were included in the future plans of most participants for municipal environmental monitoring purposes. The UAV imagery detection accuracies of litter and leaves compared to the GA results were high, 90.5% for litter and 87.5% for litter and leaves, and no statistically significant differences existed between the assessment results. Especially leaves proved challenging to detect from UAV imagery. The control group’s detection accuracies were 67.9% without and 49.0% with leaves, and with leaves the results differed with statistical significance (p = 0.028). The internal reliability of the control group was relatively high, α = 0.776 without and α = 0.805 with leaves. UAVs are deemed sufficiently accurate and versatile as monitoring and inspecting tools for municipal environmental authorities. They have the capability to complement ground assessments or, with certain prerequisites, even function as an independent monitoring method. Further application and detection method development and research on municipal UAV utilization are needed.

Food industry companies continuously develop products to stay competitive in the rapidly evolving market and to respond to changing consumer needs and desires. This study presents product development processes and approaches, design thinking, and the double diamond model, emphasizing the success of consumer-centric product development through empathetic engagement with consumers. In this qualitative research, a survey tool was developed aimed at empathetically engaging consumers through a questionnaire. The tool was constructed based on the four questions introduced by Jeanne Liedtka and Tim Ogilvie (2011) rooted in design thinking: "What is?", "What if?", "What works?", and "What wows?". Respondents were asked how they perceived the product, what delights them about it, what would make them purchase it, and what would make it perfect. The questions were operationalized through four iterations in Finnish and then presented for a hybrid sausage product concept combining meat and vegetables. The final survey received 80 responses. The responses were analyzed twice through content analysis and the natural language processing-based Etuma software. The software illustrated its capabilities and limitations in analyzing open data and identifying ideas with AI-based software. The outcomes and possibilities of the survey tool in food product development were evaluated by interviewing four professionals who have worked in food product development. The study found that the survey serves as a source of inspiration in the early stages of consumer-centric product development and facilitates empathetic engagement with consumers. Especially the first and fourth questions sparked respondents' enthusiasm for ideation, producing a diverse set of development ideas for the hybrid sausage. The AI-based software produced clarifying reports, making it easier to go through the material. The software is seen as significantly speeding up the review of extensive data, but a researcher must delve into the obtained material to identify the best ideas.