Symbiotic Urban Agriculture Networks (SUANs) are a specific class of symbiotic networks that intend to close material and energy loops from cities and urban agriculture. Private and public stakeholders in SUANs face difficulties in the implementation of technological and organisational design interventions due to the complex nature of the agricultural and urban environment. Current research on the dynamics of symbiotic networks, especially Industrial Symbiosis (IS), is based on historical data from practice, and provides only partly for an understanding of symbiotic networks as a sociotechnical complex adaptive system. By adding theory and methodology from Design Science, participatory methods, and by using agent-based modelling as a tool, prescriptive knowledge is developed in the form of grounded and tested design rules for SUANs. In this paper, we propose a conceptual Design Science method with the aim to develop an empirically validated participatory agent-based modelling strategy that guides sociotechnical design interventions in SUANs. In addition, we present a research agenda for further strategy, design intervention, and model development through case studies regarding SUANs. The research agenda complements the existing analytical work by adding a necessary Design Science approach, which contributes to bridging the gap between IS dynamics theory and practical complex design issues.
Symbiotic Urban Agriculture Networks (SUANs) are a specific class of symbiotic networks that intend to close material and energy loops from cities and urban agriculture. Private and public stakeholders in SUANs face difficulties in the implementation of technological and organisational design interventions due to the complex nature of the agricultural and urban environment. Current research on the dynamics of symbiotic networks, especially Industrial Symbiosis (IS), is based on historical data from practice, and provides only partly for an understanding of symbiotic networks as a sociotechnical complex adaptive system. By adding theory and methodology from Design Science, participatory methods, and by using agent-based modelling as a tool, prescriptive knowledge is developed in the form of grounded and tested design rules for SUANs. In this paper, we propose a conceptual Design Science method with the aim to develop an empirically validated participatory agent-based modelling strategy that guides sociotechnical design interventions in SUANs. In addition, we present a research agenda for further strategy, design intervention, and model development through case studies regarding SUANs. The research agenda complements the existing analytical work by adding a necessary Design Science approach, which contributes to bridging the gap between IS dynamics theory and practical complex design issues.
Regenerative agriculture is increasingly seen as the way forward to safeguard soil fertility and with that economic, human and natural sustainability. The fashion industry, being very much reliant on inputs from the agricultural sector, can play a pivotal role in promoting regenerative practices. In order to do so however it needs to radically rethink its business model, or else it will not be able to reap all the possible benefits.
Aeres University of Applied Sciences has placed internationalisation as a key driver in its overall strategy. By prioritising the internationalisation of education and educational consultancy the university has created solid opportunities for students, lecturers, and partners at regional, national, and international levels. Currently, more strategic development on internationalisation in applied research at Aeres is needed. There is an opportunity to utilise highly proficient researchers, state-of-the-art facilities, and an impressive national research portfolio, and for this, there is a need to develop international research agenda, a key priority for AeresResearch4EU. To address this need, Aeres University of Applied Sciences aims to strengthen its internationalisation efforts with its research activities, opening the door to many opportunities, and most importantly, creating an international research agenda spanning the university's three locations. The main objectives of AeresResearch4EU are to analyse the existing research strategy and professorships and develop them towards a global research agenda for the European Union. By focusing on international research projects, Aeres can further enhance its reputation as a leading institution for applied research in agriculture, food, environment, and green technologies. AeresResearch4EU aims to create new partnerships and collaborations with researchers and institutions across Europe, allowing Aeres to contribute to developing innovative and sustainable solutions to global challenges. With its strong commitment to internationalisation and its focus on applied research, Aeres University of Applied Sciences is poised to become an essential player in the European research landscape.
Agriculture; Macro-Micro-Macro perspective; Public goods and Public bads; Collective action; Commons; Opposite concerns; Farmers and Peasants; Anthropology
The utilization of drones in various industries, such as agriculture, infrastructure inspection, and surveillance, has significantly increased in recent years. However, navigating low-altitude environments poses a challenge due to potential collisions with “unseen” obstacles like power lines and poles, leading to safety concerns and equipment damage. Traditional obstacle avoidance systems often struggle with detecting thin and transparent obstacles, making them ill-suited for scenarios involving power lines, which are essential yet difficult to perceive visually. Together with partners that are active in logistics and safety and security domains, this project proposal aims at conducting feasibility study on advanced obstacle detection and avoidance system for low-flying drones. To that end, the main research question is, “How can AI-enabled, robust and module invisible obstacle avoidance technology can be developed for low-flying drones? During this feasibility study, cutting-edge sensor technologies, such as LiDAR, radar, camera and advanced machine learning algorithms will be investigated to what extent they can be used be to accurately detect “Not easily seen” obstacles in real-time. The successful conclusion of this project will lead to a bigger project that aims to contribute to the advancement of drone safety and operational capabilities in low-altitude environments, opening new possibilities for applications in industries where low-flying drones and obstacle avoidance are critical.
