My Research Interests

A. Collaborative Computing Paradigms for Dynamic IOT Environments

A new paradigm CCP, that exploits the present computing paradigms in a novel way, and advances the systems architecture for dynamic IOT systems. Solutions built using this mechanism are efficient, effective and productive.

My publications:
[1] Joshi, P. and Deshpande, B. (2024). Collaborative Computing Paradigms: A Software Systems Architecture for Dynamic IoT Environments. In Proceedings of the 12th International Conference on Model-Based Software and Systems Engineering – MODELSWARD; ISBN 978-989-758-682-8; ISSN 2184-4348, SciTePress, pages 297-306. DOI: 10.5220/0012473000003645

Keyword(s): Collaborative Computing Paradigms, IoT, Computing Paradigms, Cloud Computing, Edge Computing, Mist Computing, Software Architecture, Architecture Models, System Software Architecture, Collaborative Computing, Collaborating Paradigms.
Abstract: Connected systems are omnipresent, are used to monitor and control remotely, collect data and information. A variety of software systems architectures are designed which exploit computing paradigms – Edge, Fog, Mobile and Cloud – that process and analyse the data. Such an analysis is pivotal in decision making to increase operational efficiency. IoT has transformed industries like logistics, healthcare, industrial automation and agriculture and continues to refine decision making process ultimately to enhance the systems operations and efficiency. Expanding service capability of systems, has been topic of academic research and, rests on the foundation of bringing all resources in unified resource pool and make different computing facilities collaborate. Making the different computing facilities to collaborate to realise this has been part of many theoretical and experimental studies. Industry applications have adopted such systems architectures that has enhanced the applications capa bilities. This paper proposes a collaborative and unified method of system software architectures, for IoT environments, that leverage collaboration among computing paradigms. With a view to expand services, as and when needed, a unified, dynamic and distributed analytics software systems architecture was explored and experimented. Proposed collaborative method is validated through its application for vehicle and driver behaviour and data center cooling systems.

[2] Joshi, P. and Deshpande, B. (2024). A Reference Architecture for Dynamic IoT Environments Using Collaborative Computing Paradigms (CCP-IoT-RA). In Proceedings of the 19th International Conference on Software Technologies – ICSOFT; ISBN 978-989-758-706-1; ISSN 2184-2833, SciTePress, pages 193-202. DOI: 10.5220/0012863700003753

Keyword(s): IoT Reference Architecture, Collaborative Computing Paradigms, Architecture Models, System Software Architecture, Collaborative Computing, Collaborating Paradigms, Dynamic IoT Environments.
Abstract: Collaborative Computing Paradigms (CCP) has shown the potential to overcome challenges in dynamic IOT environments. CCP’s features are interconnection and interplay, dynamic distribution of data processing, fluidity of computing across paradigms, storage and data management across participating paradigms, and scalability and extendability of the systems software architecture. Reference Architecture and Models are known to provide a blueprint, that can be applied across applications domains, and thus can potentially accel-erate the development and deployment of systems software. Using the features of CCP, this paper proposes a RA for dynamic IOT environments using the collaborative computing paradigm (CCP-IOT-RA). Proposed CCP-IOT-RA reference architecture has been applied to commercial and telematics applications like building automation and vehicle and driver behaviour, demonstrating it’s versatility and effectiveness.

B. Advancing Systems Software Architectures for next generation IOT

IOT environments are challenging primarily due to its dynamism, large size (topology) and large data (heterogenous, high volume and high frequency. In addition sensing to computing to actuation is a unique ecosystem that brings numerous challenges.

C. Reconstruct Education Foundations

A comprehensive reintegration of humanities and psychology into pedagogy to revitalise education, emphasise critical thinking, creativity, and humanistic values. Ultimately, a proposed model aims to restore balance and relevance to education, aligning with industry expectations for employability.

My publications:
[1] Joshi, P (2024) Reconstruct Education Foundations: A Comprehensive Approach to Pedagogy by Reintegrating Humanities and Psychology for Richer Education. Conference: ICONWIL – International Conference on Work Integrated Learning, Hyderabad, India. DOI: 

Abstract: Historically pedagogy moved away from humanities and then also moved from psychology. This movement has had its pros and cons; which have only seen the resultant rather than anyone looking at any motivations of this separation of pedagogy. With that being the case and pedagogy being the base of nearly all matters of education; when it is looked at with the lens of how it is done today, it is moving to a set of training strategies – a move which makes education really move away from it’s core and remain focused on the skill and competency required for ultimate goal of social, economic and personal use of education. In the first part in this paper, it is argued that such a separation has a price to pay which has been quite large in today’s context. In addition the the second part is about the way the pedagogy is structured which has transformed education into training. A proposed model that emerges aims to redefine the trajectory of pedagogy for today’s educational context and landscape. It is advocated that a comprehensive reintegration of humanities and psychology (human process of learning) into the core of pedagogy can transform the model education completely. A model that aims to revive the essence of education with a pedagogy that bring a revived approach to achieve the much necessary equilibrium of key areas like skills, competencies, critical thinking, creativity, innovation and humanistic values. Finally, a view is expressed to make it relevant to bringing the expectations of the industry specifically from the view of employability.

[2] Joshi, P (2024) Surmounting Employability Challenge: A Transformative Collaborative Education Model Bridging Industry-Academia Gaps. Conference: ICONWIL – International Conference on Work Integrated Learning, April 2024, BITS Pilani, Hyderabad, India. DOI: 

Abstract: Industry and academia have always been in collaboration in numerous ways creating an overall impact for graduates at various levels. While a lot of impact is indeed created, there is always a struggle with getting “employable” candidates into the organisation. Employability, as assessed by industries, necessitates a blend of theoretical knowledge and practical skills aligned with current and future industry needs which are highly dynamic in natures and demand that students adapt quickly. Academic structures often lack direct integration of these essential components, resulting in a gap between classroom learning and industry needs. To address this gap a transformative Collaborative Education model is proposed to intertwine the theoretical knowledge and the real-world applications, specifically addressing the hard and soft skills necessary to provide students with practical exposure and problem-solving capabilities. Such a collaborative model is rooted in three primary elements – student, industry and academia and a triad of secondary elements – learning environment, teachers and mentors. Proposed six elements of the collaborative education are then applied to basically two types of students – fresh graduates and those learning during full time work. It is clear that a collaborative model does provide a much gain in the method of working and addresses the current lacuna while enhancing the system and providing a way for students to excel in the industry settings. Such a model will empower students to excel in dynamic industry environment by fostering partnerships, customised learning environments and integrated continuous improvement strategies.