Testing the Use of Crowdsourced Information: Case Study of Bike-Share Infrastructure Planning in Cincinnati, Ohio

Considering the power of web-based tools for crowdsourcing, planning organizations are increasingly using these technologies to gather ideas and preferences from the public. These technologies often generate substantial, unstructured data about public needs. However, our understanding of the use of crowdsourced information in planning is still limited. Focusing on the City of Cincinnati Bike-share planning as a case study, this article explores the challenges and considerations of using crowdsourced information. Employing mixed analysis methods, the article analyzes participant suggestions and examines whether and how those suggestions were incorporated into the bike-share plan. Interpretive analysis of interviews provided insights about suggestions that were used in the final plan. The results highlight organizational opportunities and limitations. A variety of organizational factors affected the utility of crowdsourced information in Cincinnati bike-share plan. These include the capability of the planning organizations to analyze data and facilitate participation, and the perception of planners about the value of crowdsourced information and local knowledge

Testing the Use of Crowdsourced Information: Case Study of Bike-Share Infrastructure Planning in Cincinnati, Ohio

Considering the power of web-based tools for crowdsourcing, planning organizations are increasingly using these technologies to gather ideas and preferences from the public. These technologies often generate substantial, unstructured data about public needs. However, our understanding of the use of crowdsourced information in planning is still limited. Focusing on the City of Cincinnati Bike-share planning as a case study, this article explores the challenges and considerations of using crowdsourced information. Employing mixed analysis methods, the article analyzes participant suggestions and examines whether and how those suggestions were incorporated into the bike-share plan. Interpretive analysis of interviews provided insights about suggestions that were used in the final plan. The results highlight organizational opportunities and limitations. A variety of organizational factors affected the utility of crowdsourced information in Cincinnati bike-share plan. These include the capability of the planning organizations to analyze data and facilitate participation, and the perception of planners about the value of crowdsourced information and local knowledge

Building Energy Profile Clustering Based on Energy Consumption Patterns

With the widespread adoption of smart meters in buildings, an unprecedented amount of high- resolution energy data is released, which provides opportunities to understand building consumption patterns. Accordingly, research efforts have employed data analytics and machine learning methods for the segmentation of consumers based on their load profiles, which help utilities and energy providers for customized/personalized targeting for energy programs. However, building energy segmentation methodologies may present oversimplified representations of load shapes, which do not properly capture the realistic energy consumption patterns, in terms of temporal shapes and magnitude. In this thesis, we introduce a clustering technique that is capable of preserving both temporal patterns and total consumption of load shapes from customers’ energy data. The proposed approach first overpopulates clusters as the initial stage to preserve the accuracy and merges the similar ones to reduce redundancy in the second stage by integrating time-series similarity techniques. For such a purpose, different time-series similarity measures based on Dynamic Time Warping (DTW) are employed. Furthermore, evaluations of different unsupervised clustering methods such as k-means, hierarchical clustering, fuzzy c-means, and self-organizing map were presented on building load shape portfolios, and their performance were quantitatively and qualitatively compared. The evaluation was carried out on real energy data of ~250 households. The comparative assessment (both qualitatively and quantitatively) demonstrated the applicability of the proposed approach compared to benchmark techniques for power time-series clustering of household load shapes. The contribution of this thesis is to: (1) present a comparative assessment of clustering techniques on household electricity load shapes and highlighting the inadequacy of conventional validation indices for choosing the cluster number and (2) propose a two-stage clustering approach to improve the representation of temporal patterns and magnitude of household load shapes.M.S.With the unprecedented amount of data collected by smart meters, we have opportunities to systematically analyze the energy consumption patterns of households. Specifically, through using data analytics methods, one could cluster a large number of energy patterns (collected on a daily basis) into a number of representative groups, which could reveal actionable patterns for electric utilities for energy planning. However, commonly used clustering approaches may not properly show the variation of energy patterns or energy volume of customers at a neighborhood scale. Therefore, in this thesis, we introduced a clustering approach to improve the cluster representation by preserving the temporal shapes and energy volume of daily profiles (i.e., the energy data of a household collected during 1 day). In the first part of the study, we evaluated several well-known clustering techniques and validation indices in the literature and showed that they do not necessarily work well for this domain-specific problem. As a result, in the second part, we introduced a two-stage clustering technique to extract the typical energy consumption patterns of households. Different visualization and quantified metrics are shown for the comparison and applicability of the methods. A case-study on several datasets comprising more than 250 households was considered for evaluation. The findings show that datasets with more than thousands of observations can be clustered into 10-50 groups through the introduced two-stage approach, while reasonably maintaining the energy patterns and energy volume of individual profiles

Detection of voids in welded joints using ultrasonic inspection : Quality control of welded joints in copper canisters for purpose of permanent storage of used nuclear waste

This thesis was done i cooperation with SKB Clab in Oskarshamn and studies use of sonic waves for detecting voids and irregularities in the weld joints of copper capsules used for long term storage of radioactive waste. Since these could pose material failure and thereby risk radioactive contamination of ground water it is very important to find means of quality control before storage.  During the welding procedure changes occur to the integrity of the material. The homogenous metal – in this case copper – is distorted and voids appear in and around the welded volume. A non-destructive inspection method is needed to make sure that the metal holds for the strains of long term storage. These strains are not completely known at the moment and therefore the goal of this thesis is mainly to add another tool of inspection for future studies. The tests are done using ultrasonic mapping of the welded volume. This is achieved by sending ultrasonic pulse through test samples – welded copper pieces – and recording its reflection. The recorded signals are gathered in data matrices and processed using several different signal processing methods in search of irregularities and voids. To enhance the understanding of the results a graphical user interface (GUI) is developed that allows users to visualize the results.  The welded pieces, the ultrasonic mapping and its resulting data sets were delivered to this thesis and the scope of the thesis is to develop the GUI and apply known signal processing methods to the data set.  It is shown that the irregularities do appear and that ultrasonic detection and use of the processing method is useful for quality control of the material. Further field studies are needed to identify maximum number, size and perhaps shapes of irregularities that can be within tolerance levels of the storage project. 

Detection of voids in welded joints using ultrasonic inspection : Quality control of welded joints in copper canisters for purpose of permanent storage of used nuclear waste

This thesis was done i cooperation with SKB Clab in Oskarshamn and studies use of sonic waves for detecting voids and irregularities in the weld joints of copper capsules used for long term storage of radioactive waste. Since these could pose material failure and thereby risk radioactive contamination of ground water it is very important to find means of quality control before storage.  During the welding procedure changes occur to the integrity of the material. The homogenous metal – in this case copper – is distorted and voids appear in and around the welded volume. A non-destructive inspection method is needed to make sure that the metal holds for the strains of long term storage. These strains are not completely known at the moment and therefore the goal of this thesis is mainly to add another tool of inspection for future studies. The tests are done using ultrasonic mapping of the welded volume. This is achieved by sending ultrasonic pulse through test samples – welded copper pieces – and recording its reflection. The recorded signals are gathered in data matrices and processed using several different signal processing methods in search of irregularities and voids. To enhance the understanding of the results a graphical user interface (GUI) is developed that allows users to visualize the results.  The welded pieces, the ultrasonic mapping and its resulting data sets were delivered to this thesis and the scope of the thesis is to develop the GUI and apply known signal processing methods to the data set.  It is shown that the irregularities do appear and that ultrasonic detection and use of the processing method is useful for quality control of the material. Further field studies are needed to identify maximum number, size and perhaps shapes of irregularities that can be within tolerance levels of the storage project.