COVID-19 and Digital Transformation -- Developing an Open Experimental Testbed for Sustainable and Innovative Environments (ETSIE) using Fuzzy Cognitive Maps

This paper sketches a new approach using Fuzzy Cognitive Maps (FCMs) to operably map and simulate digital transformation in architecture and urban planning. Today these processes are poorly understood. Many current studies on digital transformation are only treating questions of economic efficiency. Sustainability and social impact only play a minor role. Decisive definitions, concepts and terms stay unclear. Therefore this paper develops an open experimental testbed for sustainable and innovative environments (ETSIE) for three different digital transformation scenarios using FCMs. A traditional growth-oriented scenario, a COVID-19 scenario and an innovative and sustainable COVID-19 scenario are modeled and tested. All three scenarios have the same number of components, connections and the same driver components. Only the initial state vectors are different and the internal correlations are weighted differently. This allows for comparing all three scenarios on an equal basis. The mental modeler software is used (Gray et al. 2013). This paper presents one of the first applications of FCMs in the context of digital transformation. It is shown, that the traditional growth-oriented scenario is structurally very similar to the current COVID-19 scenario. The current pandemic is able to accelerate digital transformation to a certain extent. But the pandemic does not guarantee for a distinct sustainable and innovative future development. Only by changing the initial state vectors and the weights of the connections an innovative and sustainable turnaround in a third scenario becomes possible.Comment: 21 pages, 11 figures and 17 tables; keywords: soft computing; fuzzy cognitive maps; digital transformation; COVID-19; decision making; sustainability; integrated world system modelin

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

Development of an Adaptive Environmental Management System for Lejweleputswa District: A Participatory Approach through Fuzzy Cognitive Maps

Published ThesisEnvironmental pollution caused by mines within the district of Lejweleputswa in Free State is a major contributor to health issues and the inability to grow crops within the mining communities. Mining industries continue to develop environmental management systems/plans to mitigate the impact their operations has on the society. Even with these plans, there are still issues of environmental pollution affecting the society. Though there are Information Communication and Technology (ICT) based pollution monitoring solutions, their use is dismal due to lack of appreciation or understanding of how they disseminate information. Furthermore, non-adopting community members are being regarded as inherently conservative or irrational, but these community members argue that the recommendations and technologies brought to them are not always appropriate to their circumstances. There was concern that local people’s knowledge of their environment, farming systems, and their social as well as economic situation had been ignored and underestimated when ICTs solutions are being implemented (Warburton & Martin, 1999). Another challenge is that there is no station to monitor pollution for small communities such as Nyakallong in the district. This result in mining communities depending on their own local knowledge to observe and monitor mining related environmental pollution. However, this local knowledge has never been tested scientifically or analysed to recognize its usability or effectiveness. Mining companies tend to ignore this knowledge from the communities as it is treated like common information with no much scientific value. As a step towards verifying or validating this local knowledge, fuzzy cognitive maps were used to model, analyse and represent this linguistic local knowledge. Although this local knowledge assists in mitigating environmental pollution, incorporating it with scientific knowledge will improve its relevance, trustworthiness and acceptability by majority of community members and policy-makers. Information and Communication Technologies (ICTs) can accelerate this integration; this is the focus of this research. The increased usages of Information Technology being witnessed today makes it the most important factor for the world to depend on for solutions to many of today’s and tomorrow’s problems. These solutions make use of various forms for dissemination purposes, one of the most versatile dissemination device is a mobile phone since majority of the world’s population do own a mobile phone. In this way information is easily accessible by almost everyone that needs it. A novel environmental management solution was designed to work within the mining communities of Lejweleputswa. The research started off by designing a unique integration framework that creates the much-needed link between local knowledge and scientific knowledge. The framework was then converted into an adaptable environmental pollution management system prototype made up of three components; (1) gathering environmental pollution knowledge; (2) environmental monitoring and; (3) environmental dissemination and communication. To achieve sustainability, relevance and acceptability, local knowledge was integrated in each of the three components while mobile phones were used as both input and output devices for the system. In order to facilitate collection and conservation of local knowledge on environmental monitoring, an elaborate android-based mobile application was developed. Wireless sensor-based gas sensor boards were acquired, and deployed as a compliment to conventional monitoring stations, they were used to gather scientific knowledge. To allow for public access to the system’s data, a web portal and an SMS-based component were also implemented. In order to collect local knowledge from community, a case study of Nyakallong community in Lejweleputswa was carried out. On completion of the system prototype, it was evaluated by participants from the community; 90% of respondents gave a score of ‘excellent ‘