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Customers find the book has good insights and things they will use. However, opinions are mixed on the writing style, with some finding it fabulous and others saying it's long-winded and boring.
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Customers find the book has good insights and engaging material on helping people connect. They also say it's a fabulous guide with practical help for making the most of gatherings. Customers also say the book is eye opening and admired the author's work.
"This book is incredibly valuable for anyone whose professional or personal goals include bringing people together in a positive, intentional way...." Read more
"Parker has some interesting ideas for gathering your people , in both professional and personal settings...." Read more
"...All in all, The Art of Gathering is definitely worth the read if one is looking to be a better organizer of or participant in meetings, conferences,..." Read more
"...guide to creating gatherings that are memorable, effective and way more meaningful . Never settle for a dud party (or business meeting) again...." Read more
Customers find the book simple to implement and understand. They also say it's a beautiful, readable, and accessible guidebook.
"...Filled with clear examples and stories that make it easy to absorb and follow ." Read more
"...It's amazingly simple to bring a conversation to a whole new level with her approach...." Read more
"...meaningful friendships, it's all here in a beautiful, readable, accessible guidebook ." Read more
"This is a fresh take on how to deliberately and consciously gather people...." Read more
Customers are mixed about the writing style. Some say the book is beautifully written, while others say it's incredibly long-winded.
"The insights in this book are incredibly valuable. The writing is excellent ...." Read more
"...The author has some good, helpful points. But she’s incredibly long-winded about it ...." Read more
"...and maintaining meaningful friendships, it's all here in a beautiful, readable , accessible guidebook." Read more
"...I didn’t much care for the beginning of the book which seemed long winded and repetitive ...." Read more
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45 pages • 1 hour read
A modern alternative to SparkNotes and CliffsNotes, SuperSummary offers high-quality Study Guides with detailed chapter summaries and analysis of major themes, characters, and more.
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Introduction-Chapter 1
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Index of Terms
Important Quotes
Essay Topics
Discussion Questions
Priya Parker’s book The Art of Gathering: How We Meet and Why It Matters (2018) is a series of chapter-length essays that provide a guide to organizing effective gatherings as well as a persuasive argument for thinking about them as tools for social transformation. As a highly experienced group facilitator, advisor, podcast host, and expert in conflict resolution, Parker brings a specialist’s insight to her topic. At the same time, she organizes and presents the book as a practical, hands-on guide to help everyone from business people to community leaders to groups of friends organize purposeful gatherings. The Art of Gathering touches on a huge range of event types, from funerals to political summits. In addition, it incorporates an array of anecdotal evidence from Parker’s own experience as well as from numerous experts in professional fields including business, community organizing, entertainment, politics, and more.
This guide uses the 2018 ebook edition published by Riverhead Books, Penguin Random House. The book’s first chapter, “Decide Why You’re Really Gathering ,” lays out what Parker considers to be the most fundamental part of a successful gathering: its purpose . No gathering can be effective without a well-defined, specific purpose. Purpose, as Parker defines it, is distinct from category. While a gathering might have an obvious category, such as dinner party, business meeting, or networking event, its purpose should describe what is unique to that gathering—what makes it unlike any other.
In the next chapter, “Close Doors,” Parker makes the potentially controversial claim that gatherings should not be as inclusive as possible. When organizers choose a select group of guests/participants with care and intention, and exclude those who are not relevant to or will detract from the gathering’s purpose, then there are greater opportunities for the attendees to engage meaningfully with that purpose. Acknowledging that this perspective goes against common practice, Parker argues that being exclusive also allows for a greater effective diversity of voices within a gathering, since those who might dominate or take away from its purpose will not be present.
The third chapter, “Don’t Be a Chill Host,” challenges another commonplace recommendation. Instead of assuming that the host’s role is to stay out of the way and let a group magically congeal, Parker urges organizers to take an active role in leading gatherings. Parker deems this generous authority , since it is always conducted with an eye toward improving the experience of attendees and upholding the gathering’s purpose. In the chapter that follows, “Create a Temporary Alternative World,” Parker introduces the concept of pop-up rules . Whereas the traditional guidelines of etiquette restrict behavior, are fixed, apply to all situations, and set groups apart from others, pop-up rules apply only to the context of a gathering and are meant to encourage broad participation.
In the fifth chapter, “Never Start a Funeral with Logistics,” Parker provides some practical tips on effectively opening a gathering. She advises organizers to start with a gesture or activity that encapsulates the gathering’s purpose, rather than procedural information or generalized introductions. Parker continues these practical tips in Chapter 6, “Keep Your Best Self Out of My Gathering,” which introduces a technique she invented: 15 Toasts . This activity encourages participants in a gathering to share honest, personal insights on a theme relevant to the event’s purpose. Parker describes how she has successfully applied the 15 Toasts technique to gatherings of all kinds and sizes.
Chapter 7, “Cause Good Controversy ,” argues that introducing disagreement and debate into a gathering’s discussion can actually result in a meaningful engagement with the event’s purpose, contrary to the general rules of etiquette. Parker concedes that controversy is not necessary or appropriate for every kind of gathering, but for those attempting to solve a problem or resolve an issue, it can be a powerful tool. In the final chapter, “Accept That There Is an End,” Parker advises that closing a gathering carefully is as important as opening it with intention. An ending is the last opportunity to affirm and seal a gathering’s purpose. The chapter provides additional practical tips for doing so, such as not ending with logistical details or a long list of thank-yous.
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Humans have gathered since our first dawn as a species. We did so to share our resources and to protect one another. We’re better together than we are alone, and it’s this togetherness that has allowed us to become successful. However, because we’re so used to being together, we hardly give gathering a thought. Occasionally, when we think about gathering a few more people than normal or people who don’t know each other, we’ll ponder it a bit, but it’s more accidental than intentional. In The Art of Gathering: How We Meet and Why It Matters , Priya Parker explains that if we want to have successful gatherings, we need to put a bit of thought into it.
There’s an old African proverb (the specific source of which can’t be traced) that says, “If you want to go faster, go alone. If you want to go further, go together.” It’s at the heart of why we gather. It’s not faster. It allows us to reach further heights. Of course, there are a number of enabling conditions that must be just right for this to take place – but without the initial “together,” we can’t get there.
Conditions might include those that Kantor proposes in Reading the Room , those from William Isaacs’ work Dialogue , or the psychological safety proposed by Amy Edmondson in The Fearless Organization . Efficacy may be found best using Scott Page’s approach in The Difference or Richard Hackman’s guidance in Collaborative Intelligence .
One of the most striking ways that people were brought together was in Florence, Italy, when the Medici family gathered people with different skills and interests and allowed them to work and interact with one another. (See The Medici Effect for more.) Their efforts to bring people together kicked off the Renaissance period. We discovered that there were ways of teaming up and sharing that were effective at driving creativity and productivity. (See Team Genius for more.)
Organizations which were once plagued by ineffective meetings and who have now encountered an enlightened leader require that meetings have agendas. The agenda spells out why people are gathering, what the desired outcome is, and which items will lead to the desired outcome – at least, good agendas do this. “Wasteful meetings” is a common disdain that comes from both internal and external large corporate surveys. Too much time is wasted in meetings where there is no objective or agenda. People meet because they believe they’re supposed to meet rather than to get something specific done – or to coordinate on a specific project.
Simon Sinek in Start with Why encourages us to find the purpose before everything else. Steven Covey describes it as “first things first” in The Seven Habits of Highly Effective People .
The size of the group matters. Small groups of around six offer intimacy. Groups of 12 can build trust – and some intimacy. Groups of 30 start to create buzz and electricity. Groups of 150 are about the limit to the number of people that can feel like a single group. These numbers are consistent with Robin Dunbar’s research. (See High Orbit – Respecting Grieving .)
When planning a gathering, planning for the number of people is key to designing for the purpose of the gathering. While you may want to invite more people, sometimes those additional people can disturb the goal.
Venues come with scripts, patterns that tend to play out over and over. They’re expected, and that expectation drives more of the same. Sometimes, the patterns are so ingrained that we don’t even see they’re happening. Meet at a college, and people will expect to be lectured to – rather than engaging in a discussion. Meet in a library, and people will expect to stay quiet. (See The Public Library for more on library culture.) The coffee shop implies a casual meeting rather than one with a drive through an aggressive agenda.
When you pick the venue, you’re necessarily shaping how the interactions will happen. More than just the traffic flows and the catering options, venues veer us towards or away from our purpose.
As the host of the gathering, there’s a tension between over-controlling the event and failing to let things spontaneously emerge and under controlling the event and leaving the participants to fend for themselves. (See On Dialogue for emergence.) There’s the idea that, if you don’t structure the time, people will be left to themselves. The truer response is that they’ll be left to the mercy of the other participants – and that can have some embarrassing results.
Parker recounts an event where too much freedom was given to participants, and despite the small talk, they had managed to not get introduced to one another – and, as a result, the conversation was strained.
All gatherings are social contracts. People give up something – most notably, their precious time – and they want to know what they’ll get for it. Sometimes, it’s the opportunity to meet someone new, hold interesting discussions, or have a new experience. However, there’s always some implicit contract about what they’re giving and what they’ll be getting – or, at least, what they might get. After all, in most situations when we attend a gathering, we don’t know for sure what we will get. We get a raffle ticket and hope that our number is picked for a prize.
Failure to articulate the value proposition – or potential value proposition – for the group is a surefire way to have people fail to accept the invitation and fail to show. With group dynamics being what they are, there’s no telling what not having the right – or enough – people may do to your gathering.
Sometimes, the groups that come together can share honestly because they don’t know each other – not despite their lack of relationship. Sometimes, the things that people must share are too heavy to be borne inside of a long-term, caring relationship. They must first be tested in the waters with relative strangers to provide comfort that they may be shared with closer relationships without fear of recrimination. The strange thing about the group in which these things are shared is that they invariably end up feeling like sacred spaces. People bond and connect quickly – even if those bonds turn out to be fleeting.
For most people, the conflict in a new group is anxiety producing. Most people are conflict avoidant, and the sometimes candid and direct feedback that evolves between two or more participants in a meeting can make others duck and cover. Clearly, this doesn’t allow everyone to bring their best selves. On the other extreme, there’s the problem of groups who are too conflict avoidant, and the conflicts that the group needs to have never happen. As a result, the group gets stuck being nice and getting nothing done. Even in gatherings, we need to consider how the group dynamics are playing out, which conflicts need to happen to get out in the open, and which conflicts can be safely avoided because they can’t serve any purpose. (See Radical Candor for more.)
Kahneman explains how the Peak-End rule guides what we think of events. (See Thinking, Fast and Slow .) His research showed that the ending of any experience mattered more than it should. While endings are often left to chance, they need to be an integral part of your planning. Parker suggests that you not end with thank yous – those can be second to last. Instead, end with the thing that you want people to most remember or experience. If you do it just right, you may find that everyone has a powerful and moving experience in The Art of Gathering .
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4ir applications in the transport industry: systematic review of the state of the art with respect to data collection and processing mechanisms.
2. methodology, 2.1. search key/string approach, 2.2. source/database selection, 2.3. selection of closely related articles (inclusion and exclusion criteria), 3. related works, 3.1. general literature review, 3.2. specific literature review, 4. identified gaps, 5. discussion of findings, 6. conclusions and recommendation, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.
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S/N | Search Keywords/Strings | Number of Papers Retrieved |
---|---|---|
1. | 4IR technologies and the transportation system (4IR + technologies + transportation system) | 88 |
Impact of 4IR technologies on transportation system | ||
Application of 4IR technologies on transportation system | ||
4IR and the transportation system | ||
2. | Data collection and processing approaches in the application of 4IR technologies (data collection + processing approach + 4IR application) | 16 |
3. | Research work on transportation system and 4IR (transportation + 4IR) | 2 |
4. | Sustainable cities and urban transportation (sustainable + cities + urban + transportation) | 3 |
5. | Traffic, human driven-and electric cars, buses and trucks (traffic + human driver + electric cars) | 8 |
6. | Research articles on revolutions in the transport industry (revolutions + transport industry) | 3 |
7. | 4IR and essential services (4IR + essential services) | 4 |
8. | Sustainable transportation technologies (sustainable + transportation + technologies) | 8 |
9. | Smart and Intelligent Transportation Systems (smart + intelligent + transportation + system) | 17 |
10. | Connected Transport and Autonomous Vehicles (connected + transport + autonomous + vehicle) | 16 |
Total | 165 |
S/N | Publishing Outfit/Search Engine | Number of Papers Retrieved |
---|---|---|
1. | IEEE | 85 |
2. | Elsevier Science Direct | 36 |
3. | ACM | 1 |
4. | Taylor and Francis | 1 |
5. | Springer | 2 |
6. | Google Scholar | 40 |
Total | 165 |
S/N | Articles Accessed | Number of Papers | % |
---|---|---|---|
1. | Used | 165 | 60.4 (60) |
2. | Unused | 108 | 39.6 (40) |
Total Accessed | 273 | 100 |
S/N | Major Technology | 1st Revolution (1IR) | 2nd Revolution (2IR) | 3rd Revolution (3IR) | 4th Revolution (4IR) |
---|---|---|---|---|---|
1. | Artificial Intelligence | n/a | n/a | n/a | ✓ |
2. | Big Data | n/a | n/a | n/a | ✓ |
3. | Machine Learning | n/a | n/a | n/a | ✓ |
4. | IoT | n/a | n/a | n/a | ✓ |
5. | Blockchain | n/a | n/a | n/a | ✓ |
6. | Smart Grid | n/a | n/a | ✓ | ✓ |
7. | Cloud Computing | n/a | n/a | ✓ | ✓ |
8. | Robotics | n/a | n/a | ✓ | ✓ |
9. | Virtual and Augmented Realities | n/a | n/a | n/a | ✓ |
10. | 3D Printing | n/a | n/a | n/a | ✓ |
11. | Drones | n/a | n/a | n/a | ✓ |
12. | Fog Computing | n/a | n/a | n/a | ✓ |
13. | Internet Technology | n/a | n/a | ✓ | ✓ |
14. | Communication Technology | n/a | ✓ | ✓ | ✓ |
15. | Autonomous System | n/a | n/a | n/a | ✓ |
16. | Quantum Computing | n/a | n/a | n/a | ✓ |
17. | Electrical Technology | n/a | ✓ | ✓ | ✓ |
18. | Energy/Power Technology | ✓ | ✓ | ✓ | ✓ |
S/N | Types of 4IR Technologies | Influence and Impact | References | No of Ref. |
---|---|---|---|---|
1. | IoT/Sensor | The interconnection of vehicles, infrastructure, and users through a network of sensors and smart devices. | [ , , , , , , , , ] | 9 |
2. | Autonomous System | Improvements in autonomous vehicle performance, safety, and efficiency. | [ , , , , , , ] | 7 |
3. | Big Data | Novel techniques and methodologies that pave the way for smarter, more efficient, and user-friendly transportation systems. | [ , , , , , , , , , , , , , , ] | 15 |
4. | Artificial Intelligence | Contributes to the development and implementation of intelligent systems and control algorithms, which have revolutionized urban transportation and led to the creation of smarter and safer transportation systems. | [ , , , , , , , , , , , , , , , , , , , , , , , ] | 24 |
5. | Machine Learning/Deep Learning | Achieve predictive data analysis, optimization and decision support. Revolutionized urban transportation systems and contribute to the creation of smarter and more efficient cities. | [ , , , , , , , , , , , , , , , , , , , , , , , , , , , , ] | 29 |
6. | Computing Paradigms | Introduces innovative technologies that enhance the safety and sustainability of smart and intelligent transportation systems. | [ , , , , , , , , , ] | 10 |
7. | Geographic Information System | Enhances precision, safety, security, and satisfaction. | [ , , , , , , ] | 7 |
8. | Energy/Power Technology | Enhances environmental protection by reducing carbon emission. | [ ] | 1 |
9. | Communication Technology | Enables connectivity through faster and more reliable networks. | [ ] | 1 |
10. | Electrical Technology | Improves energy efficiency, and enables industrial automation and the development of electric vehicles. | [ , , ] | 3 |
11. | Internet Technology | Revolutionizes connectivity, and gives access to information and online services and interactions. | [ ] | 1 |
S/N | Article Ref No | Article Year | Aim | Approach | Article Contribution | Article Limitation |
---|---|---|---|---|---|---|
1. | [ ] | 2014 | To develop a prototype ITS that tracks vehicles, enables payment tickets, and analyzes crowds and ambience inside buses. | Prototype model approach using sensor, monitoring, and display systems. | Successfully developed a system that tracks/detects vehicle location, commuter information, and the ambience. | Measures implemented to safeguard the CIA of data and information were not discussed. |
2. | [ ] | 2015 | The study’s main objective was to deploy IoT technologies to build ITS in improving an urban transportation system | The authors used wireless sensors to obtain real-time traffic information. | The authors successfully developed a real-time traffic controlling and monitoring system that reduced traffic congestion in the urban area. | The authors did not approach the issues of RFID’s data reading range and data security privacy. |
3. | [ ] | 2018 | The purpose of the study is to support transportation agencies in determining the usefulness of trajectory data for their particular requirements and decision-making procedures. | ML and GPS trajectory data using V-Analytic software for visual data exploration, analysis and modelling. | The study contributed to advancing the understanding and utilization of trajectory data in road transportation systems analysis. | Factors to take into account prior to acquiring trajectory data were not considered. |
4. | [ ] | 2020 | The authors’ goal was to create a smart information system that offers all pertinent, connected information on buses, with a focus on seating arrangements. | A framework based on IoT using a touch sensor, which detects occupied and empty seats. | The authors successfully implemented a system that provides real-time information about the exact location, arrival time, and seat availability of a bus. | Waiting times and traffic congestion were not taken into consideration. The data privacy of the passenger’s location information was also an issue. |
5. | [ ] | 2020 | The aim of the study was to predict traffic congestion. | Adopts LSTM-based traffic congestion prediction approach based on the correction of missing temporal and spatial values. | The model achieved higher prediction accuracy for suburban areas, and in comparison with other relevant models. | Urban areas and low-speed zones need to be predicted in order to validate the model. |
6. | [ ] | 2021 | The authors aimed at designing a system that reduces passengers’ waiting times. | The system was implemented based on IoT technology using GPS and a microcontroller. | The implemented system was able to compute real-time information about buses (e.g., current location, arrival time, speed, etc.). | The authors were unable to implement passenger count and e-ticketing. Data privacy was also an issue. |
7. | [ ] | 2019 | To offer a framework for using big data analytics and Internet of Things (IoT) technology to design a smart transportation system. | The four layers of the system that the authors designed were data processing, the application, the network, and data gathering and acquisition. Each of these was designed to handle and process data efficiently. In the data processing layer, the authors made effective use of Spark and Hadoop to manage real-time traffic data. | A model that integrates IoT, big data analytics, and named data networking for smart transportation systems was proposed. The proposed model offers solutions to challenges such as processing big data in real time and disseminating information to citizens efficiently. | Challenges relating to data privacy and security concerns were not discussed. |
8. | [ ] | 2021 | Ton develop a model for traffic monitoring and control was the study’s goal. | The STMS model was adopted. | The study achieved superior results in the modelling of traffic congestion. | Challenges involved in implementing the model on a large scale was not discussed (e.g., data integration). |
9. | [ ] | 2021 | To present an enhanced Intelligent Transport System with roadside unit (RSU) using IoT. | The authors used Raspberry Pi Board as the main component for real-time data/information collection, while ZigBee wireless technology was used for communication. | Implemented IoT-based roadside unit for ITS with the aid of OpenCV library. | A precise vehicle count for the overlapping of vehicles was not achieved. |
10. | [ ] | 2021 | To address several IoT challenges with relative to cyber physical security, etc. | Applied geospatial modelling approach. | The authors simulated a set of geospatial indicators that support the master planning of IoT networks in facilitating the running of a Smart Transportation Security System. | Availability and quality of data. In addition, the work is limited in its generalization and may also face integration challenges. |
11. | [ ] | 2022 | The study highlights the challenges and consequences of an existing transportation system in Peshawar, in Pakistan, in response to the rapid growth in population. | IoT-based framework for busy traffic junction. | The implemented framework was able to successfully reduce travelling times, fuel consumption, and environmental pollution. | The framework was limited in the number of actors used, which could have possible effects on the effectiveness of the system in a scenario involving highly congested traffic. |
12. | [ ] | 2022 | Investigation of traffic assignment based on parking prediction. | Ensemble machine learning models were deployed to predict parking spaces after data were collected from an accumulated copy of the parking availability posted on digital signs at garages’ entrances. | Successful applicability of ensemble machine learning models in the accurate and precise prediction of ITS. | Deployment of deep learning models for a more accurate and precise prediction of ITS. |
13. | [ ] | 2022 | The article emphasizes the importance of technology selection in corporate ET strategies. | PTM framework for emerging technology selection. | A structured approach to guide engineering managers in making strategic decisions about ET adoption. | Non-establishment of more detailed criteria for PTM factors and corporate internal capabilities. |
14. | [ ] | 2023 | To obtain better clearance times and lower response times for emergency vehicles. | Adoption of unmanned aerial vehicle (UAV)-guided priority-based incident management model. | The proposed system has the potential to significantly enhance emergency response capabilities within urban transportation systems while minimizing disruption to other road users. | Real-life implementation challenge, and lack of scalability to handle larger datasets. |
15. | [ ] | 2023 | The study was designed to identify digital technology topics that are transforming the automotive industry. | Use of integrating frameworks to illustrate the value of digital technologies. | The result of the study’s use of pyLDAvis library to visualize shows that digital technologies in the automotive industry have the incremental characteristics to achieve potential in transforming the industry. | The call for a combinatorial radical (hybrid) application for implementing automotive control systems, such as collision prevention assistance technology. |
16. | [ ] | 2023 | Proposal of a lightweight machine-learning-based data collection protocol called ML-TDG. | Lightweight ML-based data collection procedure. | Presents ML-TDG as an innovative solution to address challenges in data collection and communication in urban traffic environments. | A better machine learning framework is needed to improve time, storage, energy, and communication efficiency, with possible security features incorporated. |
17. | [ ] | 2022 | To create temporal passenger profiles and to examine travel patterns. | Generative-model-based approach. | Enhanced public transportation systems. | Security of smart card data. |
18. | [ ] | 2024 | To improve energy efficiency and lower pollutant emission. | MAV virtual model. | Minimizes energy consumption. | Need to certify MAV virtual models. |
19. | [ ] | 2021 | To anticipate other vehicles’ movement and adjust driving maneuvers. | Motion-planning framework. | Guarantees the safety and replicates the actions of real drivers at junctions. | Need for more prediction accuracy. |
20. | [ ] | 2024 | To design a postprocessing pipeline to solve problems. | Simulation. | High-resolution trajectory data. | Refinement of parameters. |
21. | [ ] | 2021 | To analyze the effectiveness of on-board sensor networks. | Model for collecting delay-tolerance data for smart sensors. | Strong network coverage and connectivity. | Robust network to connect diverse smart city applications. |
22. | [ ] | 2023 | To tackle increasingly complicated traffic situations. | DL + ML. | Advancement of autonomous navigation technology. | Prediction accuracy issue. |
23. | [ ] | 2022 | To develop a reliable unsupervised learning technique for examining temporal dynamic interactions between vehicles. | Deployment of metrics on Safety Pilot DB. | Clustering efficiency. | Geometric approach. |
24. | [ ] | 2023 | Discussion of the difficulties with and development of autonomous vehicles. | Localization and mapping techniques. | Emphasizes the implication of presumptive knowledge. | Need for more reliable sensor systems. |
25. | [ ] | 2023 | To reduce wait times at terminals. | Simulation. | Increased port productivity and overall performance. | Automation and connectivity in maritime terminals. |
26. | [ ] | 2022 | To achieve vehicle detection and classification for toll management system. | Prediction with YOLOv3 algorithm. | High degree of accuracy of the deployed DL approach (YOLOv3). | Investigation of multi-scale vehicle identification. |
27. | [ ] | 2019 | To investigate free flow traffic and phantom traffic waves. | A novel technique for tracking vehicle trajectories and fuel rates. | Understanding of the effects of phantom traffic waves on fuel. | Need to corroborate results with empirical data. |
28. | [ ] | 2022 | To analyze the prospects and impacts of and difficulties in adopting autonomous vehicles. | Data retrieved from previous studies. | Enhanced energy efficiency and traffic flow. | Infrastructure and integration issues. |
29. | [ ] | 2024 | To improve the efficiency and sustainability of urban transportation. | Multi-agent reinforcement learning (MARL). | Safe, effective and sustainable transportation system. | Multi-agent lane switching. |
30. | [ ] | 2024 | To examine the effectiveness and efficiency of multi-AGV scheduling issues in warehouse picking. | Simulation. | Improved scheduling. | Needs to enhance DMAB and MAB methodologies’ resilience. |
31. | [ ] | 2024 | To create a hybrid algorithm that combines 3D k-means clustering and self-adapting genetic algorithm–particle swarm optimization. | Mixed-integer programming model. | Optimized routing problem. | The use and validation of the model in diverse settings. |
32. | [ ] | 2022 | To improve mobility and efficiency in a crowded transportation network. | Dec-CTDSP routing algorithm. | Higher performance in CAV networks. | Validation in a real-world scenario. |
33. | [ ] | 2020 | To implement routing strategies in autonomous cars. | Simulation. | High performance result. | More investigation into protocols. |
34. | [ ] | 2024 | To offer a regional route guiding system. | MPC + DRL. | Dynamic route guidance and improvement in traffic management. | Integration of real-time predictive data. |
35. | [ ] | 2024 | To examine the sustainability and moral dilemmas posed by AI-enabled urban routing for CAVs. | Review of the literature. | Support sustainable urban mobility with reduced emissions, accidents, and traffic. | Moral issues. |
36. | [ ] | 2023 | To improve the quality of digital maps for self-driving cars. | GPS + XGBoost. | Better mapping, traffic control, and scalability. | Integration of more data sources and real-time implementation. |
37. | [ ] | 2024 | To analyze observatory-action memory and learn the sequential decision-making process during lane changes. | MA-TDDPG. | Realistic lane changes and improvements in driving techniques and safety. | Multi-agent and recurrent reinforcement learning methodologies. |
38. | [ ] | 2023 | To forecast driver lane change intention. | Simulation. | Achieved higher safety and prediction accuracy. | Application of DL model. |
39. | [ ] | 2023 | To examine how different design elements and safety standards affect the operation of autonomous cars at junction. | Performance measurements + simulation model. | Improved the effectiveness and safety of roundabouts for autonomous vehicles. | Investigation of the effects of extra parameters. |
40. | [ ] | 2024 | To evaluate the variables impacting Italy’s road transport industry. | Literature review. | Offers support and opportunities to EV technology in Italy. | EV charging infrastructure. |
41. | [ ] | 2024 | To improve the sustainability of urban transportation systems. | Data from previous research. | Improved sustainability is achieved, as well as reduced accident and traffic chaos. | Environmental entropy features. |
42. | [ ] | 2024 | To create a decision-planning model for autonomous vehicles. | Fuzzy algorithm + dynamic programming. | More sustainable and safe transportation achieved. | Moral decision-making model. |
43. | [ ] | 2024 | To evaluate how biometric data affect a public transportation system. | Expert-data collection approach. | Use of model is positively correlated. | Improvement in the implementation of biometric techniques. |
44. | [ ] | 2023 | To address traffic-related issues in smart cities. | Sustainable framework, uses ITS devices and AI sensors to capture data. | Improved smart city sustainability. | Consideration of cutting-edge technologies. |
45. | [ ] | 2023 | To improve situation awareness and in-the-moment decision-making in a sustainable transportation scenario. | Distributed task-processing network + Pointer Network structure. | Improved collaborative processing and efficiency. | Algorithm optimization. |
46. | [ ] | 2023 | To improve smart mobility services. | Future mobility sensing advisor. | Enhanced urban livability and sustainability. | Newer techniques for more intelligent urban mobility solutions. |
47. | [ ] | 2023 | To improve big data analytics architecture for IoT-enabled urban ITS. | Federated Learning. | Better scalability. | Real-time adaptability. |
48. | [ ] | 2023 | To achieve a sustainable model service in deep learning. | Blockchain + IPFS. | Balanced security + system efficiency. | Investigation of supplementary technologies. |
49. | [ ] | 2022 | To guarantee seamless operation and enable effective management. | Real-time and historical data. | Improved customer experience. | Investigate additional technologies. |
50. | [ ] | 2023 | To examine and predict the causes of train delays. | GTFS data + NSW’s open data center. | Increased prediction accuracy. | Hybrid or sophisticated machine learning models. |
51. | [ ] | 2023 | To improve the accuracy of vehicle tracking. | Data collection from sensor. | Scalability and good accuracy. | Real-world circumstances. |
52. | [ ] | 2023 | To employ real-time sensory data to identify cyber-attacks on transportation networks. | Gaussian process model + LSTM-autoencoder model. | Better predictive performance. | Investigation of intricate assault scenario. |
53. | [ ] | 2024 | To estimate and forecast emissions. | Extended STIRPAT Model. | Efficiency enhancement. | Examination of supplementary impacting elements. |
54. | [ ] | 2022 | To handle the speed advisory problem in a network. | Microscopic and macroscopic methods. | Speed harmonization and emission reduction. | Computational efficiency. |
55. | [ ] | 2023 | To examine data from OECD and IEA sources and check for correlation. | Correlation analysis. | Reduced emissions. | Wider range of mitigation techniques. |
56. | [ ] | 2019 | To increase the energy efficiency of plug-in hybrid electric vehicles. | DRL. | Increased energy efficiency. | Process optimization. |
57. | [ ] | 2024 | To access energy efficiency. | Comparative analysis. | Energy-efficient surface transportation. | Enhancement of Mars exploration tactics. |
S/N | Article Ref. No | 4IR Technology | Data Collection Method/Means/Type | Processing Mechanism |
---|---|---|---|---|
1. | [ ] | IoT | NFC reader, GPS receiver, environmental sensors | Information Processing System (IPS) |
2. | [ ] | IoT | Wireless sensor, RFID, GPS | Mobile Agents & GPRS |
3. | [ ] | GPS | Trajectory data | V-Analytics Software |
4. | [ ] | IoT | Arduino Uno, GPS, sensor, IoT | IoT Module, Android App |
5. | [ ] | ML/DL | Traffic data | Long-Short Term memory (LSTM) Model |
6. | [ ] | IoT | GPS data | GPS, ESP32, Microcontroller + Wifi, Blynk IoT Platform |
7. | [ ] | IoT | Sensor data on parking lots and roadways | Hadoop and Spark |
8. | [ ] | IoT | Real-time sensor data | Data Analysis Search Engine (Simulation) |
9. | [ ] | IoT | Raspberry Pi and Zigbee serial connection | OpenCV Library |
10. | [ ] | IoT | Public infrastructure, geographic variables, metro convenience indices, national standards, 5G basic station coverage | Simulation |
11. | [ ] | IoT | Roadside unit (RSU) and IoV data | Game Theory and Nash Equilibrium |
12. | [ ] | ML/DL | Pressure sensor data | LSTM, ANN, MySQL |
13. | [ ] | Emerging technologies (ETs) | Data on ET selection criteria | Qualitative analysis |
14. | [ ] | IoT | Real-time traffic data + incident record | UAV-guided priority system |
15. | [ ] | Autonomous | Patent data on autonomous car technology | Topic modelling |
16. | [ ] | ML | ML-TDG | Apache Spark |
17. | [ ] | Autonomous | Journey transaction data collected through automated fare collection system | MaaS (Mobility-as-a-Service) |
18. | {126} | Autonomous | Data on population, traveler routes, bus stop and buses | Sophisticated scheduling and optimization techniques |
19. | [ ] | Autonomous | Data from uncontrolled crossings in Midan city | Intelligent Driver Model (IDM) and K-means clustering |
20. | [ ] | Autonomous | Simulated and real-world data | Optimization |
21. | [ ] | Smart grid | T-Drive dataset for taxi trajectories | Grid clustering algorithm, SQL, visualization |
22. | [ ] | ML/DL | Automatic identification system (AIS) data | 7 DL Models + 5 ML models |
23. | [ ] | ML | Safety pilot dataset | Clustering model |
24. | [ ] | Autonomous | Research paper data + automotive companies‘ data | Comparative analysis |
25. | [ ] | Autonomous | Data from smart edge cloud system | Automated vehicle reservation systems and advisory-based arrival system |
26. | [ ] | DL | Video photo dataset | YOLOv3 algorithm |
27. | [ ] | DL | Video data | Computer vision algorithm |
28. | [ ] | Autonomous | Traffic data | Qualitative analysis |
29. | [ ] | Autonomous | Data on vehicle placements, speed, traffic signals, and environmental factors | MARL (multi-agent reinforcement learning) algorithm |
30. | [ ] | Autonomous | Syntetic data | Simulation and comparative analysis |
31. | [ ] | Autonomous | Data from recycling center location, quantities of goods returned, recycling costs, and transportation resources | SGA-PSO (Self-adapting genetic algorithm–particle swam optimization) |
32. | [ ] | Autonomous | Data from journey time and dependability | Dec-CTDSP (Decentralized and Collaborative Time-Dependent Shortest Path) |
33. | [ ] | Autonomous | Data from traffic patterns and car counts | OMNET++ and SUMO (throughput and latency were evaluated) |
34. | [ ] | Autonomous | Real-time traffic data | MPC (model predictive control) and DRL (deep reinforcement learning) |
35. | [ ] | Artificial intelligence | Data from previous studies | Qualitative analysis |
36. | [ ] | Autonomous | GPS data | XGBoost |
37. | [ ] | Electrical technology | Large-scale real-world connected vehicle data | Multi-agent Transformer-based deep deterministic policy gradient (MA-TDDPG) model |
38. | [ ] | Autonomous | Simulated and design data | Simulation and predictive model |
39. | [ ] | Electrical technology | Data gathered from literature review, official announcements, and local laws | SWOT-AHP |
40. | [ ] | Electrical technology | Data from previous research, traffic incidents, road accidents, and real-time videos | Regression analysis |
41. | [ ] | Autonomous | Data from traffic safety, self-driving cars, and moral decision-making | Fuzzy algorithms + dynamic programming |
42. | [ ] | IoT | Data collected from domain experts | Expert analysis + statistical analysis and computations |
43. | [ ] | IoT | Automobile data from ITS devices and AI sensors | ML + cloud computing |
44. | [ ] | Blockchain | Smart contracts | Distributed task-processing network + Pointer Network structure |
45. | [ ] | IoT, big data, AI, clouds, fog, and edge computing | Fine-grained data from cloud and edge | FMSA (Future Mobility Sensing Advisor) |
46. | [ ] | IoT and Big data | Udacity self-driving car dataset | Federated Learning technique/Federated Averaging algorithm |
47. | [ ] | DL and blockchain | Smart contract | IPFS sub-networks |
48. | [ ] | Big data | Real-time and historical data (KMRL and AFC data) | ML technique |
49. | [ ] | ML | Public and open dataset (GTFS data and NSW’s Open Data Centre) | Machine model and statistical regression analysis |
50. | [ ] | IoT | 3D LiDAR data from sensor | Clustering analysis |
51. | [ ] | IoT | Real-time sensory data | Gaussian process model and LSTM-autoencoder model |
52. | [ ] | Energy technology | Data from multiple statistics year-books | Extended STIRPAT model, scenario analysis, and ridge regression |
53. | [ ] | Autonomous | Data on network speed | Microscopic and macroscopic models |
54. | [ ] | Energy technology | Data from OECD and IEA sources | Statistical and econometric techniques |
55. | [ ] | Electricity technology | Real-world data on driving circumstances, power demand, and battery state of change | Deep reinforcement learning (DRI) model |
56. | [ ] | Senergy technology | Simulated and real-world Mars exploration missions and theoretical models | Comparative analysis, using simulation and Monte Carlos |
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Ajayi, O.O.; Kurien, A.M.; Djouani, K.; Dieng, L. 4IR Applications in the Transport Industry: Systematic Review of the State of the Art with Respect to Data Collection and Processing Mechanisms. Sustainability 2024 , 16 , 7514. https://doi.org/10.3390/su16177514
Ajayi OO, Kurien AM, Djouani K, Dieng L. 4IR Applications in the Transport Industry: Systematic Review of the State of the Art with Respect to Data Collection and Processing Mechanisms. Sustainability . 2024; 16(17):7514. https://doi.org/10.3390/su16177514
Ajayi, Olusola O., Anish M. Kurien, Kareem Djouani, and Lamine Dieng. 2024. "4IR Applications in the Transport Industry: Systematic Review of the State of the Art with Respect to Data Collection and Processing Mechanisms" Sustainability 16, no. 17: 7514. https://doi.org/10.3390/su16177514
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The Art of Gathering: How We Meet and Why It Matters
The "for a reason" bit is key, for the act of bringing people together can seem like an afterthought, seldom planned through from beginning to end and a font of missed opportunities. The first step, writes the author, is "committing to a bold, sharp purpose," with milestones along the way that include plenty of reminders for why the ...
Learn more. "The Art of Gathering" is a 2018 book by Priya Parker, a facilitator and strategic advisor. The book shares insightful tips on how to make group meetings and activities more meaningful ...
The Art of Gathering is a book long overdue, and just in time." —Bruce Feiler, bestselling author of The Secrets of Happy Families and W alking the Bible "Many of the best things in life happen when people gather. So it's remarkable how little conscious intent goes into planning such moments.
In The Art of Gathering, Priya Parker gets to the heart of these questions and reveals how to design a transformative gathering. An expert on organizing successful gatherings whether in conference centres or her living room, Parker shows us how to create moving, magical, mind-changing experiences - even in spaces where we've come to expect little.
Book review: The Art of Gathering. by Elizabeth Spiegel AE. The Art of Gathering: How we meet and why it matters, by Priya Parker. We humans gather a lot. We get together for dinner parties, school reunions, weddings, funerals, workplace bonding activities … and conferences. Gatherings can be boring or invigorating, frustrating or uplifting ...
The Art of Gathering: How We Meet and Why It Matters details how advisors can practically apply NACADA's conceptual core competency on how equitable and inclusive environments are created and maintained. It provides advisors with a guide to transform ordinary events into meaningful gatherings for both students and colleagues.
An expert on organizing successful gatherings whether in conference centres, crisis zones or her living room, Parker sets forth a human-centred approach to gathering that can help us create meaningful, memorable moments - large and small, for work and play.The result is a book full of exciting real-world ideas that will forever alter the way ...
Buy The Art of Gathering: How We Meet and Why It Matters by Parker, Priya (ISBN: 9780241973837) from Amazon's Book Store. Everyday low prices and free delivery on eligible orders. The Art of Gathering: How We Meet and Why It Matters: Amazon.co.uk: Parker, Priya: 9780241973837: Books
Persuade someone to read "The Art of Gathering" in 50 words or less. ... The Book Review Podcast: Each week, top authors and critics talk about the latest news in the literary world.
A transformative exploration of the power, purpose, and benefits of gatherings in our lives: at work, at school, at home and beyond. Every day we find ourselves in gatherings, Priya Parker says in The Art of Gathering.If we can understand what makes these gatherings effective and memorable, then we can reframe and redirect them to benefit everyone, host and guest alike.
Book Review --- The Art of Gathering: How we meet and why it matters By Priya Parker. In 4th grade I had a birthday party where friends from my array of social circles at the time (school, neighborhood, gymnastics) would merge for the first time. For weeks, I was planning the games we'd play, combing through the guest list (stressed out by my ...
"A brilliant and eminently practical guide! The Art of Gathering will open your eyes to just how often we gather - and how we can turn those mundane events into dazzling opportunities for meaning, dreaming, and doing. This book should be mandatory reading for everyone from the business executive to the community activist, the conflict resolution specialist to the dinner host.
The Art of Gathering is especially recommended for professionals as they organize conferences, classrooms, and staff meetings; however, the concepts here also apply to family gatherings and celebrations. If you want to add more nonfiction to your TBR and love thinking about the "behind the scenes" of a gathering, you might enjoy this book.
The result is a book that's both journey and guide, full of exciting ideas with real-world applications. The Art of Gathering will forever alter the way you look at your next meeting, industry conference, dinner party, and backyard barbecue—and how you host and attend them. Product Details. About the Author. Read an Excerpt.
Summary. 1. Decide why you're really gathering. Define the purpose of your gathering. Everything you do speaks to that purposes, even what you do before the gathering has officially begun, like how you frame your invites, and how you describe who the gathering is for. This sets the tone and frame for the rest of what you do.
The Art of Gathering: How We Meet and Why It Matters By Priya Parker. Who's it for? According to Parker, The Art of Gathering is for those who want "to take an ordinary moment with others and make it unforgettable—and meaningful" (xiii). Liturgists (and those who plan parties with the belief that such gatherings can give us a glimpse of the feast to come) will find a few treasures of ...
The Art of Gathering is a book long overdue, and just in time." —Bruce Feiler, bestselling author of The Secrets of Happy Families and Walking the Bible "Many of the best things in life happen when people gather. So it's remarkable how little conscious intent goes into planning such moments.
PRIYA PARKER works to help people create collective meaning in their lives through gatherings. She is a master facilitator, strategic advisor, acclaimed author of The Art of Gathering: How We Meet and Why it Matters, and the host and executive producer of the New York Times podcast, Together Apart.Trained in the field of conflict resolution, Parker has worked on race relations on American ...
PRIYA PARKER works to help people create collective meaning in their lives through gatherings. She is a master facilitator, strategic advisor, acclaimed author of The Art of Gathering: How We Meet and Why it Matters, and the host and executive producer of the New York Times podcast, Together Apart.Trained in the field of conflict resolution, Parker has worked on race relations on American ...
That said, I loved some of the ideas in the book about keeping things flowing and getting people interacting. All in all, The Art of Gathering is definitely worth the read if one is looking to be a better organizer of or participant in meetings, conferences, and other formal gatherings.
Priya Parker's book The Art of Gathering: How We Meet and Why It Matters (2018) is a series of chapter-length essays that provide a guide to organizing effective gatherings as well as a persuasive argument for thinking about them as tools for social transformation.As a highly experienced group facilitator, advisor, podcast host, and expert in conflict resolution, Parker brings a specialist ...
In The Art of Gathering: How We Meet and Why It Matters, Priya Parker explains that if we want to have successful gatherings, we need to put a bit of thought into it. Go Further There's an old African proverb (the specific source of which can't be traced) that says, "If you want to go faster, go alone.
Transportation systems through the ages have seen drastic evolutions in terms of transportation methods, speed of transport, infrastructure, technology, connectivity, influence on the environment, and accessibility. The massive transformation seen in the transportation sector has been fueled by the Industrial Revolutions, which have continued expansion and progress into the fourth Industrial ...