scholarly journals Privacy-preserving AI-enabled video surveillance for social distancing: responsible design and deployment for public spaces

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nehemia Sugianto ◽  
Dian Tjondronegoro ◽  
Rosemary Stockdale ◽  
Elizabeth Irenne Yuwono
Keyword(s):  
Artificial Intelligence ◽  
Video Surveillance ◽  
Public Spaces ◽  
Privacy Preserving ◽  
Robust Performance ◽  
Implementation Framework ◽  
Content Type ◽  
Data Movement ◽  
Social Distancing

PurposeThe paper proposes a privacy-preserving artificial intelligence-enabled video surveillance technology to monitor social distancing in public spaces.Design/methodology/approachThe paper proposes a new Responsible Artificial Intelligence Implementation Framework to guide the proposed solution's design and development. It defines responsible artificial intelligence criteria that the solution needs to meet and provides checklists to enforce the criteria throughout the process. To preserve data privacy, the proposed system incorporates a federated learning approach to allow computation performed on edge devices to limit sensitive and identifiable data movement and eliminate the dependency of cloud computing at a central server.FindingsThe proposed system is evaluated through a case study of monitoring social distancing at an airport. The results discuss how the system can fully address the case study's requirements in terms of its reliability, its usefulness when deployed to the airport's cameras, and its compliance with responsible artificial intelligence.Originality/valueThe paper makes three contributions. First, it proposes a real-time social distancing breach detection system on edge that extends from a combination of cutting-edge people detection and tracking algorithms to achieve robust performance. Second, it proposes a design approach to develop responsible artificial intelligence in video surveillance contexts. Third, it presents results and discussion from a comprehensive evaluation in the context of a case study at an airport to demonstrate the proposed system's robust performance and practical usefulness.

scholarly journals To Play and To Be Played: Exploring the Design of Urban Machines for Playful Placemaking

2021 ◽  
Vol 3 ◽  
Author(s):  
Louis Chew ◽  
Luke Hespanhol ◽  
Lian Loke
Keyword(s):  
Artificial Intelligence ◽  
Urban Landscape ◽  
Active Role ◽  
Public Spaces ◽  
Active Player ◽  
Metropolitan Cities ◽  
Street Furniture ◽  
Design Case Study ◽  
Speculative Design

Within the paradigm of the smart and playable city, the urban landscape and street furniture have provided a fertile platform for pragmatic and hedonic goals of urban liveability through technology augmentation. Smart street furniture has grown from being a novelty to become a common sight in metropolitan cities, co-opted for improving the efficiency of services. However, as we consider technologies that are increasingly smarter, with human-like intelligence, we navigate towards uncharted waters when discussing the consequences of their integration with the urban landscape. The implications of a new genre of street furniture embedded with artificial intelligence, where the machine has autonomy and is an active player itself, are yet to be fully understood. In this article, we analyse the evolving design of public benches along the axes of smartness and disruption to understand their qualities as playful, urban machines in public spaces. We present a concept-driven speculative design case study, as an exploration of a smart, sensing, and disruptive urban machine for playful placemaking. With the emergence of artificial intelligence, we expand on the potential of urban machines to partake an increasingly active role as co-creators of play and playful placemaking in the cities of tomorrow.

Artificial intelligence exploitation in facility management using deep learning

2020 ◽  
Vol 20 (4) ◽  
pp. 609-624
Author(s):  
Mohamed Marzouk ◽  
Mohamed Zaher
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Life Cycle Cost ◽  
Facility Management ◽  
Support Vector ◽  
Maintenance Costs ◽  
Content Type ◽  
Protection Systems ◽  
Future Work

Purpose This paper aims to apply a methodology that is capable to classify and localize mechanical, electrical and plumbing (MEP) elements to assist facility managers. Furthermore, it assists in decreasing the technical complexity and sophistication of different systems to the facility management (FM) team. Design/methodology/approach This research exploits artificial intelligence (AI) in FM operations through proposing a new system that uses a deep learning pre-trained model for transfer learning. The model can identify new MEP elements through image classification with a deep convolutional neural network using a support vector machine (SVM) technique under supervised learning. Also, an expert system is developed and integrated with an Android application to the proposed system to identify the required maintenance for the identified elements. FM team can reach the identified assets with bluetooth tracker devices to perform the required maintenance. Findings The proposed system aids facility managers in their tasks and decreases the maintenance costs of facilities by maintaining, upgrading, operating assets cost-effectively using the proposed system. Research limitations/implications The paper considers three fire protection systems for proactive maintenance, where other structural or architectural systems can also significantly affect the level of service and cost expensive repairs and maintenance. Also, the proposed system relies on different platforms that required to be consolidated for facility technicians and managers end-users. Therefore, the authors will consider these limitations and expand the study as a case study in future work. Originality/value This paper assists in a proactive manner to decrease the lack of knowledge of the required maintenance to MEP elements that leads to a lower life cycle cost. These MEP elements have a big share in the operation and maintenance costs of building facilities.

Social distancing in a social therapy environment

2020 ◽  
Vol 41 (3/4) ◽  
pp. 113-127
Author(s):  
Geraldine Ann Akerman ◽  
Emily Jones ◽  
Harry Talbot ◽  
Gemma Grahame-Wright
Keyword(s):  
Social Isolation ◽  
Current Practice ◽  
Social Therapy ◽  
Content Type ◽  
Social Distancing ◽  
Emotional Environment ◽  
The Social ◽  
The Uk ◽  
The Impact

Purpose This paper aims to describe the impact of the COVID-19 pandemic on a prison-based therapeutic community (TC). Design/methodology/approach The paper takes the form of a case study where the authors reflect on their current practice, using the findings of research on social isolation and the overarching TC principles to explore the effect of the pandemic on the TC at HMP Grendon. The authors consider how the residents and staff adjusted to the change as the parameters changed when the social distancing rules were imposed and how they adapted to the prolonged break to therapy. Sections in the paper were written by a resident and an operational member of staff. The authors conclude with their thoughts on how to manage the consequences the lockdown has brought and start to think about what returning to “normality” might mean. Findings The paper describes the adjustments made by the residents and staff as the UK Government imposed the lockdown. The authors, including a resident and an operational member of staff comment on the psychological and practical impact these adjustments had. The thought is given to the idea of “recovery”, returning to “normality” and how this study can be best managed once restrictions are lifted. Research limitations/implications At the time of writing, there are no confirmed cases of COVID-19 at HMP Grendon. The measures and commitment from all staff and residents in the prison to keep the prison environment safe may in part account for this. This paper explores the effects of lockdown on the emotional environment in a TC and highlights the consequences that social isolation can have on any individual. To the authors’ knowledge, there is currently no research undertaken on the impact of lockdown/social isolation on a TC. This research would be useful, as the authors postulate from reflections on current practice that the effects of the lockdown will be greater in a social therapy environment. Originality/value HMP Grendon started in 1962, as this time there have been no significant events that have meant the suspension of therapy for such a sustained period. It is, therefore, important that the impact of such is considered and reflected upon.

Modelling near-real-time order arrival demand in e-commerce context: a machine learning predictive methodology

2020 ◽  
Vol 120 (6) ◽  
pp. 1149-1174 ◽  
Author(s):  
K.H. Leung ◽  
Daniel Y. Mo ◽  
G.T.S. Ho ◽  
C.H. Wu ◽  
G.Q. Huang
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Real Time ◽  
Service Providers ◽  
Series Data ◽  
Illustrative Case ◽  
Implementation Framework ◽  
Inference System ◽  
Content Type

PurposeAccurate prediction of order demand across omni-channel supply chains improves the management's decision-making ability at strategic, tactical and operational levels. The paper aims to develop a predictive methodology for forecasting near-real-time e-commerce order arrivals in distribution centres, allowing third-party logistics service providers to manage the hour-to-hour fast-changing arrival rates of e-commerce orders better.Design/methodology/approachThe paper proposes a novel machine learning predictive methodology through the integration of the time series data characteristics into the development of an adaptive neuro-fuzzy inference system. A four-stage implementation framework is developed for enabling practitioners to apply the proposed model.FindingsA structured model evaluation framework is constructed for cross-validation of model performance. With the aid of an illustrative case study, forecasting evaluation reveals a high level of accuracy of the proposed machine learning approach in forecasting the arrivals of real e-commerce orders in three different retailers at three-hour intervals.Research limitations/implicationsResults from the case study suggest that real-time prediction of individual retailer's e-order arrival is crucial in order to maximize the value of e-order arrival prediction for daily operational decision-making.Originality/valueEarlier researchers examined supply chain demand, forecasting problem in a broader scope, particularly in dealing with the bullwhip effect. Prediction of real-time, hourly based order arrivals has been lacking. The paper fills this research gap by presenting a novel data-driven predictive methodology.

Investigation of spatial configuration management on social distancing of recreational clubhouse for COVID-19 in Penang, Malaysia

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nur Adibah Binti Abdul Nasir ◽  
Ahmad Sanusi Hassan ◽  
Fatemeh Khozaei ◽  
Muhammad Hafeez Bin Abdul Nasir
Keyword(s):  
Spatial Organization ◽  
Spatial Configuration ◽  
Management Strategies ◽  
Spatial Arrangement ◽  
Public Spaces ◽  
Disease Spread ◽  
Content Type ◽  
Factors Affecting ◽  
Social Distancing ◽  
The Impact

PurposeSince the appearance of COVID-19 social distancing and staying home have been recommended repeatedly by the governments for disease prevention. As the challenge continues to remain the current study seeks to examine the factors affecting social distancing through space planning and management. More specifically the current study aims to examine the appropriateness of the spatial organization and space configuration of a clubhouse with a linear plan layout in the mitigation of the spread of infections due to serious pandemic COVID-19.Design/methodology/approachFor an enhanced understanding of the impact of spatial arrangements of public spaces plan on the effective implementation of social distancing this study has used the space syntax analysis method. The MPSP clubhouse building in Penang, Malaysia was selected as the case study. The level of permeability and wayfinding were determined in the building plan and were illustrated using photoshop software to depict the interrelation between the indoor spaces and building circulation. Graphs of the depth of space were used to analyze the level of permeability and wayfinding to illustrate the possibility of social distancing in the plan.FindingsThe result of the study shows the significant role of proper plan layout design on social distancing. While clear and direct wayfinding can positively be associated with more effective social distancing, the inefficient design of user access, inappropriate locations of multiple entry and exit and indefinite directions of users' inside buildings can impose slight limitations. The average level of permeability might suggest ineffective spatial arrangement, ignoring the needs of spatial segregation. The study further found that the linear plan layouts with proper zoning and effective management strategies can be considered a proper layout to facilitate social distancing and the spread of COVID-19.Originality/valueThe current study is unique in terms of examination of the spatial configuration of linear public spaces plan layout for possible temporary adaptability to curb disease spread during the unexpected advent of a pandemic. Based on researchers' best of knowledge it is the first time that the impact of recreational space design on social distancing has been examined. The study also originally sheds light on the fact that the commonly used guideline for the social distancing of 1–2 m between 2 persons, in reality, is practically inadequate given the nature of the sports activities.

Artificial Intelligence powered Internet of Things and smart public service

2019 ◽  
Vol 38 (1) ◽  
pp. 165-179 ◽  
Author(s):  
Ying Ma ◽  
Kang Ping ◽  
Chen Wu ◽  
Long Chen ◽  
Hui Shi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Public Service ◽  
Smart Cities ◽  
Machine Learning Algorithms ◽  
The Internet ◽  
Content Type ◽  
Academic Fields ◽  
The Internet Of Things

Purpose The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent years as well. AI naturally combines with the Internet of Things in various ways, enabling big data applications, machine learning algorithms, deep learning, knowledge discovery, neural networks and other technologies. The purpose of this paper is to provide state of the art in AI powered IoT and study smart public services in China. Design/methodology/approach This paper reviewed the articles published on AI powered IoT from 2009 to 2018. Case study as a research method has been chosen. Findings The AI powered IoT has been found in the areas of smart cities, healthcare, intelligent manufacturing and so on. First, this study summarizes recent research on AI powered IoT systematically; and second, this study identifies key research topics related to the field and real-world applications. Originality/value This research is of importance and significance to both industrial and academic fields researchers who need to understand the current and future development of intelligence in IoT. To the best of authors’ knowledge, this is the first study to review the literature on AI powered IoT from 2009 to 2018. This is also the first literature review on AI powered IoT with a case study of smart public service in China.

Artificial intelligence in the defense sector: an RBV and isomorphism perspectives to the case of the Lebanese Armed Forces

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Charbel Chedrawi ◽  
Yara Atallah
Keyword(s):  
Artificial Intelligence ◽  
Armed Forces ◽  
Sensitive Data ◽  
Content Type ◽  
Study Approach ◽  
Interview Guide ◽  
Innovation And Technology ◽  
Depth Interviews

Purpose This paper aims to dynamically analyze the opportunities and challenges of AI in the defense sector in Lebanon or any security agency or any organization with sensitive data through a resource-based view perspective, the adoption of artificial intelligence (AI)/narrow AI applications in the Lebanese Armed Forces (LAF) and to diagnose the current strategic orientation toward innovation and technology within the LAF while avoiding isomorphism. Design/methodology/approach The methodology is based on a qualitative interpretive case-study approach collected from several departments of the LAF. In fact, there is a developing convention to use qualitative research approaches among which case studies to study information technology phenomena (Trauth and Jessup, 2000; Benbasat et al., 1987; Klein and Meyers, 1999). Data were collected through centered semi-structured in-depth interviews (two to three hours each) with an interview guide coded abductively between the researchers and the interviewees conducted in numerous departments of the LAF with their top officials and generals (O1, O2, O3…); the anonymity of the interviewees was kept due to the sensitivity of the data collected, which took place between September 2018 and March 2019. Data consolidation and processing were conducted using NVivo. Findings This paper shows that the LAF is undeniably facing many challenges among which isomorphism caused by the lack of resources; it also shows that narrow AI applications provide new avenues for the LAF to avoid such institutional isomorphism. Originality/value The role of narrow AI in limiting isomorphism in the defense sector.

scholarly journals China’s AI Strike Force on COVID-19

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wilson Kia Onn Wong
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Full Potential ◽  
Case Study Approach ◽  
Content Type ◽  
Study Approach ◽  
The World ◽  
Remarkable Progress ◽  
Made In

PurposeThis paper examines the methodical and highly efficacious manner in which China deployed its comprehensive AI (artificial intelligence) strategy to significantly stymie the spread of COVID-19 across the country.Design/methodology/approachThis study deploys a case-study approach, supported by the literature on existing and emerging AI and related technologies.FindingsThe onset of the COVID-19 pandemic has revealed to the world the remarkable progress China has made in AI and its accompanying ecosystem. More importantly, this outlier event demonstrates the surgical, hybridised manner in which China has utilised these emerging technologies in containing its spread (i.e. “AI Epidemiological Targeting”) and set itself on the path to unleashing their full potential (i.e. “AI Symbiosis Paradigm”). Nonetheless, China still needs to harness its rapidly advancing AI prowess in identifying COVID-19's pathogenesis and developing a proven vaccine.Originality/valueThis study presents a pioneering effort to analyse the deployment of AI and its ecosystem in the “war” against COVID-19.

Monitoring Social Distancing Using Artificial Intelligence for Fighting COVID-19 Virus Spread

2021 ◽  
Vol 12 (3) ◽  
pp. 48-63
Author(s):  
Hashem Alyami ◽  
Wael Alosaimi ◽  
Moez Krichen ◽  
Roobaea Alroobaea
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Saudi Arabia ◽  
Public Spaces ◽  
Virus Spread ◽  
Person Detection ◽  
Social Distancing ◽  
Backbone Network ◽  
Health Authorities ◽  
Public Health Authorities

To restrict COVID-19, individuals must remain two meters away from one another in public since public health authorities find this a healthy distance. In this way, the incidence of “social distancing” keeps pace with COVID-19 spread. For this purpose, the proposed solution consists of the development of a tool based on AI technologies which takes as input videos (in real time) from streets and public spaces and gives as output the places where social distancing is not respected. Detected persons who are not respecting social distancing are surrounded with red rectangles and those who respect social distancing with green rectangles. The solution has been tested for the case of videos from the two Holy Mosques in Saudi Arabia: Makkah and Madinah. As a novel contribution compared to existent approaches in the literature, the solution allows the detection of the age, class, and sex of persons not respecting social distancing. Person detection is performed using the Faster RCNN with ResNet-50 as it is the backbone network that is pre-trained with the open source COCO dataset. The obtained results are satisfactory and may be improved by considering more sophisticated cameras, material, and techniques.

COVID-19 and “the trinity of boredom” in public spaces: urban form, social distancing and digital transformation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hisham Abusaada ◽  
Abeer Elshater
Keyword(s):  
Urban Form ◽  
Public Spaces ◽  
Digital Transformation ◽  
Added Value ◽  
Widespread Application ◽  
Content Type ◽  
Social Distancing ◽  
Urban Planning And Design ◽  
The Face ◽  
The Trinity

PurposeOver the coming decades, the widespread application of social distancing creates challenges for the urban planning and design profession. This article aims to address the phenomenon of boredom in public places, its main influences that generate change in repetition, monotony and everyday lifestyle, whether positive, negative or both – depending on the binding and governing rules of urban shape variations and daily lifestyles.Design/methodology/approachThis viewpoint relied on literary narration to discuss the phenomenon of boredom vis-à-vis urban design and placemaking solutions in the face of social distancing. It builds its orientation by analyzing the works of nine scholars and five of their relevant theories.FindingsEvidence from previous studies helped develop three-pillar guidelines that can produce better results for post-pandemic development in the face of boredom. These pillars include recommendations for the trinity of heterogeneity for metamorphosis in urban form, changes in public life and digital transformation in a time of uncertainty on how to confront (un)seen boredom in public spaces. Practitioners should develop new insights into the relationship between people and place by reviewing existing paradigms in urban studies to avoid repetition, monotony and change in everyday life after a pandemic.Originality/valueThe added value here is in underlining boredom as one of the consequences of social distancing and lockdown applications building on the phenomenon's theorizers. The key contribution of this work is the three-pillar recommendation for confronting the boredom in public spaces that happens because of social distancing and lockdown.

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