TY - CHAP A1 - Völkl, Jakob A1 - Melzer, Matthias A1 - Dünnweber, Jan A1 - Sarkar, Amitrajit T1 - Dynamic Route Planning for a Data Collecting Luggage Transport Service T2 - 18th IEEE International Conference on Control & Automation, June 18-21, 2024, Reykjavík, Iceland N2 - Control and Automation of services of the urban infrastructure offered to citizens and tourists are elementary parts of a smart city. But both rely on a stable supply of data from sensors spread across the whole city, e. g., the fill level sensors of waste bins needed for a waste management tool which we developed in a collaboration with the Regensburg city council for the on-demand collection of waste bins. Europe has a lot of historic cities like Regensburg with narrow streets and huge building walls, some made from granite and fieldstones, which often represents an insurmountable obstacle to wireless data transmission. The reduction of the road traffic volume poses an additional challenge for city planners. By means of networked planning and simulation software, the situation, state and efficiency of citywide logistic services can be monitored and optimized. In the course of such optimizations, we propose the combination of digital and logistic services. As an example, we show that monitoring state information, such as the waste bin fill levels, can be accomplished using the same vehicles and the same planning software, that is used for luggage transportation. Moreover, we describe how we adapted a solver for a variant of the TSP, namely the prize-collecting traveling salesman, to optimize the route planning dynamically. Y1 - 2024 PB - IEEE ER - TY - CHAP A1 - Burger, David A1 - Sarkar, Amitrajit A1 - Kirsch, Konstantin A1 - Dünnweber, Jan ED - Bouzas Lorenzo, Ramón T1 - Combining Fill-Level Sensing with Route Optimization for a More Efficient Waste Collection T2 - ECDG 2018 - European Conference on Digital Government, 2018, Santiago De Compostela, Spain N2 - We tackle the problem that collecting all the waste of modern cities within the scheduled time spans becomes increasingly challenging, while the waste collection team is not supplemented accordingly in many places, e.g. by more staff or vehicles. Separating waste has become natural for urban populations, as recycling is ecologically necessary. However, the separation also leads to a continuously increasing number of containers which are logistically unmanageable without computer-aided collection scheduling. Regensburg recently introduced a new program for the collection of biological waste, which extends the private collection of such waste by a few hundred public biological waste containers. Computer support was pretty basic so far, i.e. the collection times were recorded and the routes were sporadically rescheduled manually in an Excel sheet. We show that much shorter waste collection routes can be found automatically using a dynamic version of the classic Ant Colony Optimization (ACO) algorithm for shortening the collection routes. Moreover, we sketch an loT (lnternet-of-Things) approach to "lntelligent Waste Containers" which we equip with ultrasonic sensors monitoring the fill levels, which allows us to skip poorly used containers during the collection and reposition them on demand. By means of a computer simulation with online visualization, we illustrate that our optimized and dynamically adapted collection routes lead to significant time savings. Indeed, more than twice the number of currently used containers can be collected within the same time. We also report about the first experiments that we conducted with real sensors. The presented work is the result of a cooperation between four contributing parties: 1) Technical University of Regensburg (OTH); 2) Ara Institute of Canterbury; 3) Regensburg's Governmental Department of Waste Management; and 4) an industry partner (kpit.com). We compare the outcome of our project with related work and we sketch some future perspectives and ideas for transforming Regensburg into an even more automatized, environmentally friendly "smart city". KW - smart city KW - loT KW - wireless sensor networks KW - smart government KW - e-waste KW - Ant Colony Optimization Y1 - 2018 SN - 9781912764037 SP - 24 EP - 31 ER - TY - CHAP A1 - Dünnweber, Jan A1 - Sarkar, Amitrajit A1 - Puthiyadath, Vimal Kumar A1 - Barde, Omkar ED - Saeed, Khalid ED - Dvorský, Jiří T1 - A Tale of Four Cities - Improving Bus and Waste Collection Schedules in Practical Smart City Applications T2 - Computer Information Systems and Industrial Management N2 - Computer-based Improvements of waste collection and public transport procedures are often a part of smart city initiatives. When we envision an ideal bus network, it will primarily connect the most crowded bus stops. Similarly, an ideal waste collection vehicle will arrive at every container exactly at the time when it is fully loaded. Beyond doubt, this will reduce traffic and support environmentally friendly intentions like waste separation, as it will make more containers manageable. A difficulty of putting that vision into practice is that vehicles cannot always be where they are needed. Knowing the best time for arriving at a position is not insufficient for finding the optimal route. Therefore, we compare four different approaches to optimized routing: Regensburg, Christchurch, Malaysia, and Bangalore. Our analysis shows that the best schedules result from adapting field-tested routes frequently based on sensor measurements and route optimizing computations. KW - Smart city KW - Bus schedules KW - Waste management Y1 - 2021 SN - 978-3-030-84340-3 U6 - https://doi.org/10.1007/978-3-030-84340-3_30 SP - 369 EP - 380 PB - Springer CY - Cham ER - TY - CHAP A1 - Stadler, Timo A1 - Sarkar, Amitrajit A1 - Dünnweber, Jan ED - Saeed, Khalid ED - Dvorský, Jiří T1 - Bus Demand Forecasting for Rural Areas Using XGBoost and Random Forest Algorithm T2 - CISIM2021: 20th International Conference on Computer Information Systems and Industrial Management Applications, September 24-26 2021, Ełk, Poland N2 - In recent years, mobility solutions have experienced a significant upswing. Consequently, it has increased the importance of forecasting the number of passengers and determining the associated demand for vehicles. We analyze all bus routes in a rural area in contrast to other work that predicts just a single bus route. Some differences in bus routes in rural areas compared to cities are highlighted and substantiated by a case study data using Roding, a town in the rural district of Cham in northern Bavaria, as an example. Data collected and we selected a random forest model that lets us determine the passenger demand, bus line effectiveness, or general user behavior. The prediction accuracy of the selected model is currently 87%. The collected data helps to build new mobility-as-a-service solutions, such as on-call buses or dynamic route optimizations, as we show with our simulation. KW - Transportation KW - Rural mobility KW - Prediction KW - Öffentlicher Personennahverkehr KW - Ländlicher Raum KW - Verkehrsnachfrage KW - Prognosemodell KW - Random Forest Y1 - 2021 SN - 978-3-030-84340-3 U6 - https://doi.org/10.1007/978-3-030-84340-3_36 SP - 442 EP - 453 PB - Springer CY - Cham ER - TY - CHAP A1 - Sarkar, Amitrajit A1 - Traubinger, Thomas T1 - IS Resilience Decision Priorities at German SMEs BT - A Q-Method Approach T2 - 27th American Conference on Information Systems 2021 (AMCIS 2021): Digital Innovation and Entrepreneurship, Virtual Conference, August 9-13, 2021 N2 - IS resilience addresses the challenge of securing organizational information systems against disruptions to ensure the continuation of daily business processes and to guarantee the resilience of the organization as a whole. In this paper, we adopt Agency Theory and Weill’s IT Governance framework to investigate the decision priorities of senior executives in the context of IS resilience planning, which falls under the broader umbrella of IT governance. The management of IS resilience involves different fields of action types and interests which decision-makers within organizations must confront. This is of special importance for small- to medium-sized companies (SMEs) where IS often is not a dedicated or small corporate function. This paper identifies distinctive character types of corporate decision-makers at SMEs in a European context and their priorities in IS resilience. The study was performed using Q-methodology. It was able to identify and describe three additional types of decision-makers in comparison to previous research thereby clearly showing that the field has progressed. These character types provide an informative insight into the priorities of IS resilience planning in SMEs and show differences and commonalities between decision-makers. Y1 - 2021 UR - https://aisel.aisnet.org/amcis2021/strategic_is/strategic_is/19/ ER -