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Enhancing Traffic Incident Management and Regulatory Compliance Using IoT and Itms: A Mumbai Traffic Police Case Study
In the rapidly urbanizing landscape of Mumbai, a megacity confronted with significant traffic management and law enforcement challenges, the deployment of an advanced city surveillance system represents a transformative approach to urban governance. This paper examines the integration of over 11,000 CCTV cameras into the Mumbai Traffic Police's operational framework, covering an area of 438 square kilometers encompassing 41 traffic divisions and 94 police stations. Since its inception in 2016, the system has been pivotal in enhancing safety, order, and mobility within the city, especially amid obstacles such as ongoing infrastructure projects, traffic congestion, accidents, and natural disasters. Central to this study is the analysis of the Mumbai City Surveillance System Project (MCSP), which leverages CCTV technology to generate and classify Incident Reports (IR) based on severity, ranging from minor disruptions to significant emergencies. The period from October 2021 to 2023 saw a marked increase in IR generation, from 742 reports in 2021 to 10,392 in 2022 and 9,639 in 2023, indicating the system's growing efficacy in real-time traffic management and incident response.This paper further explores the cutting-edge integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies within the MCSP framework, highlighting the role of computational intelligence in enhancing the capabilities of Intelligent Transportation Systems (ITS). By employing AI-driven predictive analytics, the system effectively anticipates traffic conditions based on diverse variables such as traffic flow, vehicle speed, and weather, thereby optimizing traffic management strategies.The findings underscore the significant impact of AI and IoT technologies in redefining urban transportation networks, demonstrating improved efficiency, safety, and resilience in the face of Mumbai's complex transportation challenges. This study contributes to the discourse on smart city initiatives, offering insights into the role of advanced computational technologies in facilitating intelligent transportation solutions and shaping the future of urban living. 2024 IEEE. -
Revolutionizing Road Traffic Management and Enforcement: Harnessing AI, ML, and Geospatial Techniques
This study investigates the synergistic application of Artificial Intelligence (AI), Machine Learning (ML), and Geospatial Technologies in optimizing traffic management systems. Through a mixed-methods research design, it evaluates the potential of these technologies to enhance urban traffic flow and reduce congestion. The research emphasizes the critical importance of data quality, ethical considerations, and the selection of appropriate technological solutions based on specific urban traffic scenarios. Findings highlight the significant role of integrated AI and geospatial analyses in improving traffic predictions and operational efficiency. Future work will focus on developing more sophisticated models that ensure privacy, equity, and adaptability to new transportation trends. 2024 IEEE. -
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A Spatio-temporal Model for the Analysis and Classification of Soil Using the IoT
The Internet of Things (IoT) is an evolving trend in the field of computer applications where various hardware and software are connected together to address a specific problem. With the help of the IoT, the world has become smart and enabled itself to connect various objects (e.g., cars, computers, mobile phones, and smart appliances) with distinctive Internet protocol addresses, which allows them to interact with one another, thus accomplishing various procedures. Applications of the IoT include but are not restricted to smart cities, healthcare, industry, and robotics. Amongst a huge list of applications furnished by the IoT, agricultural IoT is the theme of this chapter. The IoT in agriculture transforms entities such as crops, soils, and livestock in a smart way by utilizing underlying technologies such as embedded systems, pervasive computing, sensor networks, ubiquitous computing, ad hoc networks, various wireless communication technologies, Internet protocols and other advanced technologies. The research here focuses on the most important agriculture entity soil. It is the soil that determines the yield of a crop. The more fertile the soil, more qualitative is the yield. The main idea behind the research is to identify the soil most suitable for agriculture. Using a spatio-temporal model, the soil samples collected from various parts of the country are classified into agricultural soil and non-agricultural soil. This classification is done by the aid of features such as the pH of the soil, and its humidity, moisture, and temperature collected from IoT sensors. The chapter begins with an introduction to the usage of IoT technology in different areas of agriculture followed by an account of the proposed state-of-the-art model, and its results, analysis, and a conclusion. 2022 selection and editorial matter, Vikram Bali, Vishal Bhatnagar, Deepti Aggarwal, Shivani Bali, and Mario JosDiv; individual chapters, the contributors. -
Link stability - based optimal routing path for efficient data communication in MANET
The paper delves into the complexities of Mobile Ad hoc Networks (MANETs), which consist of a diverse array of wireless nodes. In such networks, routing packets poses a significant challenge due to their dynamic nature. Despite the variety of techniques available for optimizing routing in MANETs, persistent issues like packet loss, routing overhead, and End-to-End Delay (EED) remain prevalent. In response to these challenges, the paper proposes a novel approach for efficient Data Communication (DC) by introducing a Link Stability (LS)-based optimal routing path. This approach leverages several advanced techniques, including Pearson Correlation Coefficient SWIFFT (PCC-SWIFFT), Galois-based Digital Signature Algorithm (G-DSA), and Entropy-based Gannet Optimization Algorithm (E-GOA). The proposed methodology involves a systematic process. Initially, the nodes in the MANET are initialized to establish the network infrastructure. Subsequently, the Canberra-based K Means (C-K Means) algorithm is employed to identify Neighboring Nodes (NNs), which are pivotal for creating communication links within the network. To ensure secure communication, secret keys (SK) are generated for both the Sender Node (SN) and the Receiver Node (RN) using Galois Theory. Following this, PCC-SWIFFT methodologies are utilized to generate hash codes, serving as unique identifiers for data packets or routing information. Signatures are created and verified at the SN and RN using the G-DSA. Verified nodes are subsequently added to the routing entry table, facilitating the establishment of multiple paths within the network. The Optimal Path (OP) is selected using the E-GOA, considering factors such as link stability and network congestion. Finally, Data Communication (DC) is initiated, continuously monitoring LS to ensure optimal routing performance. Comparative analysis with existing methodologies demonstrates the superior performance of the proposed model. In summary, the proposed approach offers a comprehensive solution to enhance routing efficiency in MANETs by addressing critical issues and leveraging advanced algorithms for key generation, signature verification, and path optimization. 2024, Universitas Ahmad Dahlan. All rights reserved. -
A Framework for Integrating the Distributed Hash Table (DHT) with an Enhanced Blooms Filter in MANET
MANET, a self-organizing, infrastructure-less, wireless network is a fast-growing technology in day-to-day life. There is a rapid growth in the area of mobile computing due to the extent of economical and huge availability of wireless devices which leads to the extensive analysis of the mobile ad-hoc network. It consists of the collection of wireless dynamic nodes. Due to this dynamic nature, the routing of packets in the MANET is a complex one. The integration of distributed hash table (DHT) in MANET is performed to enhance the overlay of routing. The node status updating in the centralized hash table creates the storage overhead. The bloom filter is a data structure that is a space-effective randomized one but it allows the false-positive rates. However, this can be able to compensate for the issue of storage overhead in DHT (Distributed hash table). Hence, to overcome the storage overhead occurring in DHT, and reduce the false positives, the Bloom's filter is integrated with the DHT initially. Furthermore, the link stability is measured by the distance among mobile nodes. The optimal node selection should be done for the transmission of packets which is the lacking factor. If it fails to select the optimal path then the removal of malicious nodes may lead to the unwanted entry of nodes into the other clustering groups. Therefore, to solve this problem, the bloom's filter is modified for enhancing the link stability. The novelty of this proposed work is the integration of Bloom's filter with the Distributed Hash Table which provides good security on transmission data by removing false-positive errors and storage overhead 2022,International Journal of Advanced Computer Science and Applications.All Rights Reserved -
Efficient data mining techniques for medical data
Healthy decision making for the well being is a challenge in the current era with abundant information everywhere. Data mining, machine newlinelearning and computational statistics are the leading fields of study that are supporting the empowered individual to take valuable decisions to optimize the outcome of any working domain. High demand for data newlinehandling exists in healthcare, as the rate of increase in patients is proportional to the rate of population growth and life style changes. Techniques for early diagnosis and prognosis prediction of diseases are the need of the hour to provide better treatment for the human community. Data mining techniques are a boon for building a quality and newlineefficient model for health prediction applications. As cancer explodes everywhere in recent years, the data sets from cancer newlineregistries have been focused as the medical data in this research. The main aim of thesis is to build a constructive and efficient classifier model for cancer prognosis prediction. Most of the existing system develops a diagnosis prediction models from the screening or survey data, as the data newlineset is widely available and are easy to collect due the insensitive nature of newlinethe factors involved in such research. Whereas the prognosis prediction requires a sensitive details of the patients those who are under treatment for a diagnosed disease. Hospitals and the community registries newlinemaintained by the government are the main source for data collection. Well maintained electronic hospital records with histopathology information is not public in India for the researchers. Hence cancer data newlinefrom a US based open access data center has been used in this research for all experimentation. This research work is a progressive model that gradually improves the newlineprediction accuracy by selecting appropriate data mining techniques in each phase. -
Prominent label identification and multi-label classification for cancer prognosis prediction
Cancer prognosis prediction improves the quality of treatment and increases the survivability of the patients. Conventional methods of cancer prediction deal with single class by limiting the prognosis prediction to one response variable. The SEER Public Use cancer database has more prominent variables that support better prediction approach. The objective of this paper is to find the prominent labels from cancer databases and use them in a multi-class environment. The implementation consist of three phases namely, pre-processing, prominent label identification and multi-label classification. Breast, Colorectal and Respiratory Cancer Data sets have been used for the experimentation. Also random samples from all three data sets are generated to form a mixed cancer data. Patient survival, number of primaries and age at diagnosis are the prominent labels identified from others using the Decision tree, Nae Bayes and KNN algorithms. The three prominent labels have been tested using multi-label RAkEL algorithm to find the relations between them. The results of the empirical study are comparatively better than the traditional way of cancer prediction. 2012 IEEE. -
Survey on Malicious URL Detection Techniques
Crimes in the cyberspace are increasing day by day. Recent cyber threat defense reports states that 80.7% of the systems are compromised at least once in 2020. Cyber criminals taking the pandemic situation as an opportunity for the mass attack through malicious URL circulated by email or text messages in social media. Performing cyber-attacks through malicious URLs is the handy method for the cyber criminals. Protecting from such attacks requires proper awareness and solid defense system. Some of the common approaches followed by the cybercriminals to deceive the victims are 1. Phishing URLs which is very similar to the legitimate URLs. 2. Redirecting URLs 3. Using JavaScript, redirects to the phishing URL when user interacts with webpage 4. Social engineering etc. As soon as the novice internet users clicks on the malicious URL link, cyber criminals can easily steal personal information or install malware on their device to get additional access. Recently malicious URLs are generated algorithmically and uses URL shortening service to evade the existing security setup such as firewall and web filters. In literature, the researchers have proposed several ways to detect the malicious URLs but, new attack vectors that are introduced by the cyber criminals can easily bypass the security system. The purpose of this paper is to provide an overview of various malicious URL detection techniques which includes blacklist based, rules based, machine learning and deep learning-based techniques. Most importantly, the paper discusses the common features used by the detection system from webpages to classify the URL as malicious or benign and various performance metrics. This will encourage the new researchers to bring out the innovative solutions. 2022 IEEE. -
Labor unrest at Wistron Corporation India plant What went wrong?
Learning outcomes: After completion of this case study, students/managers will be able to analyze reasons for the labor unrest at Wistron Corporations Indian manufacturing plant; examine the implementation of labor regulations applicable to the employment of contract workers by Wistron Corporation; infer the problems associated with rapid expansion in the workforce; analyze the labor regulatory challenges faced by Wistron Corporation; and demonstrate problem-solving skills. Case overview/synopsis: The focus of this case study was the crisis faced by Apples contract manufacturer Wistron Corporation due to labor unrest, riots and violence in its production facility located near Bangalore in India. This case study discussed the CEOs dilemma in resolving the crisis and regaining the confidence of stakeholders, namely, the contract employees, Apple Inc. and the State Government of Karnataka. To give the readers an overview of the crisis this case discussed in detail the underlying reasons for the labor unrest such as a rapid increase in manpower, unilateral increase in working hours without extra pay, unjustified pay cuts, understaffed and underqualified human resources (HR) department, ill-equipped attendance and payroll system. It also gave an overview of mistakes in labor management that could be avoided by a manufacturing firm. The case also discussed the pressure faced by the Wistron CEO due to probation and a new business freeze by Apple Inc. This case study is suitable for understanding the complexities of labor laws and the legal complications that can arise when a corporation disregards local labor laws while operating in foreign countries. Complexity academic level: The case is best suited for postgraduate and executive MBA students studying labor law, industrial psychology and HR management in commerce and business management streams. The authors suggest that the instructor should inform students to read the case study before attending the 90-min session. It can be executed in the classroom after discussing the theoretical concepts. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2024, Emerald Publishing Limited. -
Influence of Consumers Self Perception on Devaluation of Ugly Produce Marketing Strategies to Reduce Food Waste in the Indian Context
Ugly produce refers to aesthetically imperfect fruits and vegetables and also fruits and vegetables with minor blemishes. Ugly produce does not refer to spoilt, rotten, or germ-infected fruits and vegetables. The basic premise of this study is from self-signaling and self-perception theories. The self-signaling theory states that when people make a choice, they disclose something of their character and personality not just to others, but also to themselves. Self-perception theory (SPT) developed by psychologist Daryl Bem asserts that people develop their attitudes by observing their own behavior and further concluding what attitudes must have caused it. Classically, consumers undervalue ugly produce because of altered self-perceptions; simply visualizing the consumption of imperfect produce acts as a self-indicative signal that negatively affects how consumers view themselves. Due to this, the unattractive produce, even though perfectly edible and with the same taste and nutritional value, is rejected by consumers merely based on shape or some other cosmetic blemish. We discussed the strategies adopted by Indian startups and organizations to reduce food waste. Deep discounting is the strategy followed by food retailers worldwide to sell ugly produce, however, this is not the best strategy as it leads to losses for both the retailers as well as the farmers. We suggested alternative strategies successfully followed by foreign retailers, such as spreading awareness, boosting self-confidence and esteem among consumers, attracting kids, etc., which can be followed by Indian food retailers for selling ugly fruits and vegetables. 2022, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Crisis Faced by a B-School
This article discusses the marketing missteps made by a prestigious B-school, exploring key concepts such as improper positioning and the imperative for repositioning. It provides an in-depth analysis of the decline in admissions at this well-established institution, culminating in a crisis. Additionally, the article explores a range of strategies available to the B-schools founder and top management team to enhance the institutions visibility and bolster its brand. Furthermore, it sheds light on the challenges the B-school faces, including inadequate infrastructure and other weaknesses, such as subpar research output, moderate placement offers and a low ranking in national B-school surveys. The case meticulously examines the errors made by the B-schools leadership team, such as discontinuing advertising and the ill-advised decision to withdraw from B-school surveys. Ultimately, this article epitomizes the predicament faced by an institution that relied on its historical strengths and failed to adapt to the evolving demands of its environment. It concludes by presenting short-term and long-term strategies available to decision-makers for crisis mitigation. It highlights digital marketing as one of the short-term solutions earnestly considered by the B-schools management to enhance brand awareness among its target audience. 2024 Lahore University of Management Sciences. -
Desiri Naturals: sustainable agriculture and eco-friendly business
Learning outcomes: After completion of the case study, the students will be able to critically analyze the business model of Desiri Naturals, analyze the pricing strategy of Desiri Naturals, examine the importance of experiential marketing in the success of an environment-friendly business, identify the challenges faced by new entrepreneurs and evaluate the sustainability practices of Desiri Naturals. Case overview/synopsis: This case study discusses the business model of an environmentally friendly business. The challenges and obstacles faced by entrepreneurs are illustrated in this case. The entrepreneurs vision to provide chemical-free food is highlighted and their business operations as a means to fulfill this vision are explained. Desiri used an age-old bull-driven method of oil extraction (Ghana). Challenges in pricing due to the availability of low-priced mass-produced edible oil using the solvent extraction process are presented in this case. The entrepreneurs faced the pricing dilemma at the inception of the business, as oil produced using the natural cold pressing method cost three times the selling pricing of solvent-extracted oil. Innovative methods of experiential marketing such as Ghana tourism are explained in this case. This case study also explains the sustainable and natural farming techniques propagated through its network of farmers. This case study provides insights into the scalability of this model and the scope for employment generation in rural India. The environmentally friendly practices followed by Desiri, such as the use of glass bottles and reusable steel containers for packaging oil are emphasized. Finally, this case presents the marketing and operational challenges faced by entrepreneurs in their quest to expand their operations. Complexity academic level: This case study can be used by postgraduate and undergraduate students studying marketing, entrepreneurship, sustainability and operations management courses in commerce and business management streams. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS8: Marketing. 2024, Emerald Publishing Limited. -
Zomatos dilemma a case of disgruntled delivery partners at Zomato
Learning outcomes: This case study provides students/managers an opportunity to learn about:??Learning objective 1: Critically analyse reasons for the disgruntlement of delivery partners of Zomato.??Learning objective 2: Evaluate Zomatos moral obligations to gig workers in the absence of government regulations.??Learning objective 3: Analyse the drivers of well-being affecting e-commerce delivery partners.??Learning objective 4: Evaluate the welfare schemes undertaken by Zomato for its delivery partners and infer well-being measures that can be adopted to improve worker engagement. Case overview/synopsis: The focus of this case was the crisis at Zomato as a result of the protests by gig workers engaged as delivery partners at the company. This case discussed the CEOs dilemma in resolving the crisis. Zomato's business model was discussed to provide students an overview of the dynamics and challenges of online food delivery business; the companys initiatives to enhance the robustness of its business model and the resulting media backlash questioning some of these initiatives that could endanger the lives of its delivery partners. In addition, this case explored the lack of regulatory provisions for gig workers in India. Finally, the options available to the protagonist to mitigate the crisis were discussed. The focal point was the well-being initiatives that the protagonist could consider implementing to address the concerns voiced by the delivery partners and encourage them to engage in Zomato's business with positivity. Complexity academic level: The case is best suited for postgraduate and executive students studying Human Resources subjects in Commerce and Business Management streams. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2022, Emerald Publishing Limited. -
Zomato Instant - "10-Minute Delivery Plan" Controversy
[No abstract available] -
Good-looking step in bad direction RBI Internal Working Group proposal
Learning outcomes: After discussing this case, the authors expect that the students will have the following learnings: critically analyse the latest Reserve Bank of India (RBI) banking proposal, which was proposed by the Internal Working Group (IWG) in November 2020. Understand concepts such as connected lending, crony capitalism and financial crisis. Have a basic idea about the Banking Regulations Act, 1949 and regulatory framework in the Indian banking sector. Case overview/synopsis: This case is an analysis of the recent RBI proposal on banking regulations in India. The authors have referred secondary data in terms of published papers by stalwarts and experts in the banking and economics field. This case analyses the pros and cons of the IWG proposal to RBI governing body. The case also touches upon interesting banking and macroeconomics concepts. What makes this case interesting is that RBI is open to receive comments from all the stakeholders till January 2021. Complexity academic level: Applicable to undergraduate and postgraduate students studying banking and finance specialisation in commerce and business management streams. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 1: Accounting and Finance. 2021, Emerald Publishing Limited. -
Pricing and content Netflixs dilemma in India
Learning outcomes: The learning outcomes of this study are as follows:1. Analyze the pricing strategy followed by Netflix in India;2. Examine the challenges faced by media companies, including over-the-top (OTT) service providers, in developing content for target consumers in emerging markets; and3. Evaluate the dynamics of the Indian OTT industry and understand the effect of external and internal factors on the growth of Netflix in India. Case overview/synopsis: This case discusses the dilemma faced by Netflix in India regarding pricing and content. Netflix was accused of hurting the religious and political sentiments of Indians by broadcasting bold shows such as Sacred Games and A Suitable Boy. Netflix is caught in a dilemma between its pursuit to achieve its target of achieving 100 million subscribers from India versus continuing its profitable high pricing strategy. Another key dilemma is regarding the streaming of attractive bold content which may occasionally hurt the religious/political sentiments of some Indians or stream only safe content which may be deemed as boring by its young target audience. Complexity academic level: Undergraduate and postgraduate students studying Marketing courses in Commerce and Business Management streams can use this case. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 8: Marketing. 2022, Emerald Publishing Limited. -
Coca-Cola product placement strategy backfires a case of celebrity activism
Research methodology: A secondary research method was used to collect data for this case. The authors have made use of newspaper articles and published articles written by journalists and experts which are available in the public domain. Case overview/synopsis: Instances of celebrity activism such as athlete activism are rising. Social media has amplified the voice of celebrities and given them a personal channel to directly communicate with their fans without any media censorship. The same is true especially concerning endorsement by sports superstars, who now seem to have a mind of their own, independent of the official line of clubs, tournament organizers or sponsoring companies. This case discusses the embarrassment and financial loss faced by soft drinks giant Coca-Cola due to the public snub by football superstar Cristiano Ronaldo during an official press conference of the EURO 2020 championship. Complexity academic level: Undergraduate and postgraduate students studying marketing management and brand management courses in business management and commerce streams can use this case. This case can also be used for marketing specialization students at the undergraduate and postgraduate levels. 2023, Emerald Publishing Limited. -
Mass layoffs at BYJUS founders dilemma
Learning outcomes: This case study provides students/managers an opportunity to learn about the following: to infer the challenges involved in the downsizing of employees; to asses and evaluate BYJUS organizational culture; and to determine the impact of workplace toxicity. Case overview/synopsis: The focus of this case is the controversy faced by BYJUS due to its mass layoffs and toxic work culture. This case discusses the CEOs dilemma in resolving the controversy. Two rounds of mass layoffs at BYJUS are discussed in detail. The industrial dispute filed by Employees Union against BYJUS accusing it of denying due compensation to laid-off employees is also discussed. This case consists of a section explaining the toxic work culture at BYJUS, which is supported by employee complaints. The CEOs justification and apology have been illustrated in this case. The case ends with a closing dilemma and challenges faced by the CEO. Complexity academic level: The case is best suited for undergraduate students studying Human Resources Management subjects in Commerce and Business Management streams. The authors suggest that the instructor inform students to read the case before attending the 90-min session. It can be executed in the classroom after discussing the theoretical concepts. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2024, Emerald Publishing Limited. -
Enhancing Transparency and Trust in Agrifood Supply Chains through Novel Blockchain-based Architecture
At present, the world is witnessing a rapid change in all the fields of human civilization business interests and goals of all the sectors are changing very fast. Global changes are taking place quickly in all fields manufacturing, service, agriculture, and external sectors. There are plenty of hurdles in the emerging technologies in agriculture in the modern days. While adopting such technologies as transparency and trust issues among stakeholders, there arises a pressurized necessity on food suppliers because it has to create sustainable systems not only addressing demandsupply disparities but also ensuring food authenticity. Recent studies have attempted to explore the potential of technologies like blockchain and practices for smart and sustainable agriculture. Besides, this well-researched work investigates how a scientific cum technological blockchain architecture addresses supply chain challenges in Precision Agriculture to take up challenges related to transparency traceability, and security. A robust registration phase, efficient authentication mechanisms, and optimized data management strategies are the key components of the proposed architecture. Through secured key exchange mechanisms and encryption techniques, client's identities are verified with inevitable complexity. The confluence of IoT and blockchain technologies that set up modern farms amplify control within supply chain networks. The practical manifestation of the researchers' novel blockchain architecture that has been executed on the Hyperledger network, exposes a clear validation using corroboration of concept. Through exhaustive experimental analyses that encompass, transaction confirmation time and scalability metrics, the proposed architecture not only demonstrates efficiency but also underscores its usability to meet the demands of contemporary Precision Agriculture systems. However, the scholarly paper based upon a comprehensive overview resolves a solution as a fruitful and impactful contribution to blockchain applications in agriculture supply chains. Copyright 2024 KSII.