Enhancing pharmaceutical packaging through a technology ecosystem to facilitate the reuse of medicines and reduce medicinal waste

The idea of reusing dispensed medicines is appealing to the general public provided its benefits are illustrated, its risks minimized, and the logistics resolved. For example, medicine reuse could help reduce medicinal waste, protect the environment and improve public health. However, the associated technologies and legislation facilitating medicine reuse are generally not available. The availability of suitable technologies could arguably help shape stakeholders’ beliefs and in turn, uptake of a future medicine reuse scheme by tackling the risks and facilitating the practicalities. A literature survey is undertaken to lay down the groundwork for implementing technologies on and around pharmaceutical packaging in order to meet stakeholders’ previously expressed misgivings about medicine reuse (’stakeholder requirements’), and propose a novel ecosystem for, in effect, reusing returned medicines. Methods: A structured literature search examining the application of existing technologies on pharmaceutical packaging to enable medicine reuse was conducted and presented as a narrative review. Results: Reviewed technologies are classified according to different stakeholders’ requirements, and a novel ecosystem from a technology perspective is suggested as a solution to reusing medicines. Conclusion: Active sensing technologies applying to pharmaceutical packaging using printed electronics enlist medicines to be part of the Internet of Things network. Validating the quality and safety of returned medicines through this network seems to be the most effective way for reusing medicines and the correct application of technologies may be the key enabler

Indoor Positioning for Monitoring Older Adults at Home: Wi-Fi and BLE Technologies in Real Scenarios

This paper presents our experience on a real case of applying an indoor localization system formonitoringolderadultsintheirownhomes. Sincethesystemisdesignedtobeusedbyrealusers, therearemanysituationsthatcannotbecontrolledbysystemdevelopersandcanbeasourceoferrors. This paper presents some of the problems that arise when real non-expert users use localization systems and discusses some strategies to deal with such situations. Two technologies were tested to provide indoor localization: Wi-Fi and Bluetooth Low Energy. The results shown in the paper suggest that the Bluetooth Low Energy based one is preferable in the proposed task

Scan to BIM for 3D reconstruction of the papal basilica of saint Francis in Assisi In Italy

The historical building heritage, present in the most of Italian cities centres, is, as part of the construction sector, a working potential, but unfortunately it requires planning of more complex and problematic interventions. However, policies to support on the existing interventions, together with a growing sensitivity for the recovery of assets, determine the need to implement specific studies and to analyse the specific problems of each site. The purpose of this paper is to illustrate the methodology and the results obtained from integrated laser scanning activity in order to have precious architectural information useful not only from the cultural heritage point of view but also to construct more operative and powerful tools, such as BIM (Building Information Modelling) aimed to the management of this cultural heritage. The Papal Basilica and the Sacred Convent of Saint Francis in Assisi in Italy are, in fact, characterized by unique and complex peculiarities, which require a detailed knowledge of the sites themselves to ensure visitor’s security and safety. For such a project, we have to take in account all the people and personnel normally present in the site, visitors with disabilities and finally the needs for cultural heritage preservation and protection. This aim can be reached using integrated systems and new technologies, such as Internet of Everything (IoE), capable of connecting people, things (smart sensors, devices and actuators; mobile terminals; wearable devices; etc.), data/information/knowledge and processes to reach the desired goals. The IoE system must implement and support an Integrated Multidisciplinary Model for Security and Safety Management (IMMSSM) for the specific context, using a multidisciplinary approach

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

Design Creativity: Future Directions for Integrated Visualisation

The Architecture, Engineering and Construction (AEC) sectors are facing unprecedented challenges, not just with increased complexity of projects per se, but design-related integration. This requires stakeholders to radically re-think their existing business models (and thinking that underpins them), but also the technological challenges and skills required to deliver these projects. Whilst opponents will no doubt cite that this is nothing new as the sector as a whole has always had to respond to change; the counter to this is that design ‘creativity’ is now much more dependent on integration from day one. Given this, collaborative processes embedded in Building Information Modelling (BIM) models have been proffered as a panacea solution to embrace this change and deliver streamlined integration. The veracity of design teams’ “project data” is increasingly becoming paramount - not only for the coordination of design, processes, engineering services, fabrication, construction, and maintenance; but more importantly, facilitate ‘true’ project integration and interchange – the actualisation of which will require firm consensus and commitment. This Special Issue envisions some of these issues, challenges and opportunities (from a future landscape perspective), by highlighting a raft of concomitant factors, which include: technological challenges, design visualisation and integration, future digital tools, new and anticipated operating environments, and training requirements needed to deliver these aspirations. A fundamental part of this Special Issue’s ‘call’ was to capture best practice in order to demonstrate how design, visualisation and delivery processes (and technologies) affect the finished product viz: design outcome, design procedures, production methodologies and construction implementation. In this respect, the use of virtual environments are now particularly effective at supporting the design and delivery processes. In summary therefore, this Special Issue presents nine papers from leading scholars, industry and contemporaries. These papers provide an eclectic (but cognate) representation of AEC design visualisation and integration; which not only uncovers new insight and understanding of these challenges and solutions, but also provides new theoretical and practice signposts for future research

Fireground location understanding by semantic linking of visual objects and building information models

This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

Sustainable Strategic Urban Planning: Methodology for Urban Renovation At District Level

Sustainable urban renovation is characterized by multiple factors (e.g. technical, socio-economic, environmental and ethical perspectives), different spatial scales and a number of administrative structures that should address the evaluation of alternative scenarios or solutions. This defines a complex decision problem that includes different stakeholders where several aspects need to be considered simultaneously. In spite of the knowledge and experiences during the recent years, there is a need of methods that lead the decision-making processes. In response, a methodology based on the global idea and implications of working towards a more sustainable and energy efficient cities as a holistic procedure for urban renovation at district level is proposed in the European Smart City project CITyFiED. The methodology has the energy efficiency as main pillar and the local authorities as client. It is composed of seven phases that ensures an effective dialogue among all the stakeholders, aiming to understand the objectives and needs of the city to define a set of Strategies for Sustainable Urban Renovation and their integration within the Strategic Urban Planning of the cities.This project has received funding from the European Union’s Seventh Programme for research, technological development and demonstration under grant agreement N° 609129. The authors would like to thank the rest of the partners of the CITyFiED project for their help and support

ACon: A learning-based approach to deal with uncertainty in contextual requirements at runtime

Context: Runtime uncertainty such as unpredictable operational environment and failure of sensors that gather environmental data is a well-known challenge for adaptive systems. Objective: To execute requirements that depend on context correctly, the system needs up-to-date knowledge about the context relevant to such requirements. Techniques to cope with uncertainty in contextual requirements are currently underrepresented. In this paper we present ACon (Adaptation of Contextual requirements), a data-mining approach to deal with runtime uncertainty affecting contextual requirements. Method: ACon uses feedback loops to maintain up-to-date knowledge about contextual requirements based on current context information in which contextual requirements are valid at runtime. Upon detecting that contextual requirements are affected by runtime uncertainty, ACon analyses and mines contextual data, to (re-)operationalize context and therefore update the information about contextual requirements. Results: We evaluate ACon in an empirical study of an activity scheduling system used by a crew of 4 rowers in a wild and unpredictable environment using a complex monitoring infrastructure. Our study focused on evaluating the data mining part of ACon and analysed the sensor data collected onboard from 46 sensors and 90,748 measurements per sensor. Conclusion: ACon is an important step in dealing with uncertainty affecting contextual requirements at runtime while considering end-user interaction. ACon supports systems in analysing the environment to adapt contextual requirements and complements existing requirements monitoring approaches by keeping the requirements monitoring specification up-to-date. Consequently, it avoids manual analysis that is usually costly in today’s complex system environments.Peer ReviewedPostprint (author's final draft