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An Integrated Home Monitoring System of a Scalable IoT Architecture Using UDP and TCP Connections
No full textThe advancement of the Internet of Things (IoT) provides a set of new possibilities and challenges within the Industrial and Manufacturing environments, as well as into the Private Sector and daily life in our houses. In this context it is important to design and provide an IoT integrated system with scalable architecture while maintaining a set of competitive costs and performance. This paper presents the development of an IoT-based Smart Home Temperature and Humidity Monitoring System. The proposed architecture aims to demonstrate core IoT principles such as real-time data collection, remote device control, and scalable architecture using Arduino Uno R4 Wi-Fi and ESP32 microcontrollers. The system successfully simulated appliance control - e.g., radiators, extractor fans - via LEDs and basic actuators, combined with a mobile application providing real-time environmental data - e.g., temperature, humidity, Carbon Monoxide (CO) levels - and remote-control functionality. Challenges included hardware compatibility, power management, and software integration, with further work on security features (i.e. cryptography algorithms) and cloud integration
Cultural Stations of Disability: A Moment in Discourse
No full textIn the disability community, which can have multiple meanings in itself, we often experience poignant moments in sociocultural discourse. Our pathways to knowledge and understanding of identity are defined by life’s landmarks, many of which resonate with what thereby become formative figures or artefacts. This mapping of key moments involves recognising, and reflecting upon, cultural stations of disability.
More than being demarcations of disruption to the normative social order, cultural stations of disability sometimes pertain to its very epitome. They hold something of a moment in discourse with which identification is paramount but variously emotive. They may capture feelings of liberation to which we joyfully return, difficult memories that we revisit to ponder, or the nadir of modernity from which we can only hope to learn.
In this edited volume, an international gathering of contributors finds and defines dozens of cultural stations of disability in music, art, film, television programs, literature, sitcom, activism, sport, performance, organisations, places, and events.
Cultural Stations of Disability: A Moment in Discourse will be of interest to interdisciplinary readers in disability studies, humour studies, media studies, film studies, television studies, literary studies, gender studies, cultural studies, popular music studies, and related disciplines in the humanities, education, and social sciences
Lessons learned: Teachers’ perceptions of incorporating police expertise into PSHE lessons
Full text linkThis article presents the findings of an initial evaluation of an innovative contribution by West Yorkshire Police (WYP) to Personal, Social, Health, and Economic (PSHE) teaching in schools within the region, namely the Police-Education (Pol-Ed) programme. Pol-Ed contributes police specific knowledge into the PSHE curriculum with the aim of keeping children safe from crime and victimisation. This article details the findings of a mixed-methods study using ten semi-structured interviews and an online questionnaire (
n
= 94) with PSHE teachers in West Yorkshire to explore their perceptions of the Pol-Ed programme. Additionally, we explore this type of expert-informed teacher resource to contribute to the school PSHE curriculum in a meaningful way. The quantitative results suggest that teachers perceived that Pol-Ed helps them teach children how to keep safe, understand risks and the law, and to make positive choices. The qualitative findings suggest that teachers perceived that Pol-Ed increases pupils’ awareness of risk of crime and victimisation, is locally relevant, builds trust and strengthens community relations, and supports teacher confidence, knowledge, and awareness. We conclude by offering some reflections on the potential of this type of programme to add value to the school curriculum in a range of ways by sharing of expertise across organisations
Educative mentoring: Exploring the articulation and enactment of the concept of educative mentoring with mentors and student teachers
Full text linkEffective mentoring is an essential cornerstone when supporting the progress and development of teachers right from the start of their careers. Despite an abundance of initiatives intended to support this, concern remains over teacher recruitment and retention. This case study explored six mentor pairs’ (school mentor and student teacher) articulation and enactment of ‘educative mentoring’. This is where the mentor and student teacher operate within a constructivist-oriented model of mentoring, developing a partnership where the mentor and student teacher engage in a joint enquiry into the pedagogy of what is going on in the classroom; practices such as co-planning, looking at
children’s work and encouraging the student teacher and mentor to justify their practice are employed. Three research questions were set:
1. What perceptions do mentors and student teachers have of mentoring and educative mentoring in particular?
2. What educative mentoring practices are enacted by mentors and student teachers during the mentoring relationship?
3. What supports the mentor relationship to be conducive to educative mentoring?
Data were collected by online semi structured interviews with each mentor and student teacher. This was then followed by, for each mentor pair, the observation of a mentor meeting, a lesson delivered by the student teacher and the lesson debrief. The data were analysed using Braun and Clarke’s (2022) Reflexive Thematic Analysis. From this analysis the following four findings were discussed further:
1. None of the participants recognised the term educative mentoring but when educative mentoring was explained to them, all the participants could give examples from practice of educative mentoring practices.
2. Educative mentoring practices that could be articulated by the participants during their interview, were observed in practice (mentor meeting or lesson debrief) as well as practices that had not been articulated.
3. The relational aspects of mentoring, dominated both the mentors’ and student teachers’ perceptions of mentoring but this element of mentoring appeared to be more important to student teachers than their mentors.
4. The characteristics and experiences of the mentor pairs and ‘mentorability’ of the student teacher, did appear to influence the enactment of educative mentoring practices.
The findings suggest that educative mentoring is one way mentoring can be strengthened by the establishment of collaborative reciprocity between the mentor and student teacher. The following facilitate this: adopting the student teacher into the school community, mentors that can justify their pedagogy and develop a pedagogical relationship with the student teacher and develop a bi focal lens. A future longitudinal study working with mentors as they develop
these and their enactment of educative mentoring is recommended
Maritime Transport and Supply Chain Resilience
No full textThis book addresses maritime transport and supply chain resilience, offering analysis of emerging topics as well as case studies from different countries and regions
Analysis of the impact of climate-driven extreme weather events (EWEs) on the UK train delays: A data-driven BN approach
Full text linkClimate change exacerbates the occurrence of frequent Extreme Weather Events (EWEs), directly disrupting railway operations in numerous countries, notably the United Kingdom. Projections for the UK climate indicate an increase in rainfall intensity, warmer and wetter winters, hotter and drier summers, and more frequent and intense EWEs. Such climatic shifts cause increased weather-related railway delays, which in turn result in significant economic loss. This study develops a new risk model using a data-driven Bayesian Network (BN) to analyse the impact of climate-induced EWEs on UK train delays. The model quantifies the influence of various factors on delays, providing deeper insights into their individual and combined effects. The new model and the f indings contribute to the disclosure of 1) the interconnections among the different variables influencing train delays, including the origin and destination of the train and traction type, and 2) the prediction of the quantitative extent to which the variables can jointly lead to train delays of different severity levels, incident reason, the month of occurrence, the responsible operator, and the train schedule type. Critical findings highlight the substantial negative impact of severe flooding on the operational reliability of the UK railway system. An important insight was the significant clustering of delays ranging from 80 to 90 min, particularly on Fridays, suggesting the need for targeted operational interventions in specific regions. Additionally, the analysis identified December as the most hazardous month for train delays due to EWEs, with January and July also showing elevated risk levels. This paper offers valuable insights for transport planners, enabling them to prioritise climate-related scenarios causing the most severe train delays and to formulate the associated adaptation measures and strategies rationally
Interactive Conversational AI with IoT Devices for Enhanced Human-Robot Interaction
Full text linkSignificance - The rapid advancements in conversational AI and IoT technologies have opened up new possibilities for human-machine interaction. Despite the progress, a gap exists in integrating these two fields to create more centralized, intuitive, and engaging user experiences. Current integrations typically consist of specialized hardware-software pairs that do not fully leverage the capabilities of advanced conversational models, thereby limiting their applicability. This research proposes a general solution to bridge the capabilities of various IoT devices with the oversight and control abilities of AI language models, enhancing the potential for more versatile and natural IoT-AI-human interactions.
Aim and Approach - This research presents the design and development of an IoT system operated by an AI language model and conversationally managed by humans to operate robots. Based on this setup, the initial goal is to create a framework for interactively controlling a robotic arm. The approach involves using a Raspberry Pi as a central control system and ChatGPT API to manage conversations and execute given commands.
Results - The developed IoT-AI system demonstrated efficient and reliable human-robot interaction where the user can entertain a conversational interaction with the robotic arm. It effectively captures user voice inputs, processes them through advanced AI models, and generates appropriate commands for the robotic arm, achieving an average voice-to-motion latency of 5.5 s. An example of commands are “engage arm”, “move right 20” (i.e. move the robotic arm to the right of 20 cm) combined with more conversational commands such as “can you hear me?”, “what’s your name?”. While some latency and voice recognition challenges exist, the overall performance confirms the viability of using conversational AI for natural and intuitive robotic control.
Conclusions - This research successfully integrates conversational AI with IoT devices, resulting in a more user-centric and efficient human-robot interaction. The system highlights the significant potential of precisely translating natural language commands into robotic actions, enhancing user experience and operational efficiency
Understanding Psychological Wellbeing Among Iranian Healthcare Workers: The Role of Resilience and Social Capital
Full text linkBackground: Psychological wellbeing is a protective factor against mental disorders. This study aimed to clarify the contribution of resilience and social capital as predictors of psychological well-being as a first step to developing evidence-based interventions to improve psychological wellbeing in healthcare workers.
Methods: This cross-sectional study was conducted on Iranian healthcare workers. Systematic random sampling was used to recruit 140 employees working in healthcare centers in Shiraz, Iran in 2021. Data was collected using a survey that included Ryff’s Scale of Psychological Well-being, the Social Capital at Work scale, and the Resilience at Work scale. Data analysis involved correlations and path analysis to clarify the relationship between predictor variables for psychological well-being in healthcare workers.
Results: Significant relationships were found between psychological well-being and resilience (r=0.29, P<0.01), psychological well-being and social capital (r=0.31, P<0.01), and resilience and social capital (r=0.42, P<0.01). Path analysis revealed a significant and direct relationship between social capital to resilience (β=0.56, P=0.001) and from resilience to psychological well-being (β=0.59, P=0.001). The direct path from social capital to psychological well-being was insignificant (β=0.00, P=0.93). The model explained 36% of the variance in psychological well-being.
Conclusion: Resilience was the most influential predictor of psychological well-being. It was associated with psychological well-being both directly and indirectly through the contribution of social capital. Promoting individual empowerment and developing of resilience skills should be considered an essential approach in designing and implementing intervention programs to improve the psychological well-being of healthcare workers
