Role of Digitalization in Election Voting Through Industry 4.0 Enabling Technologies

The election voting system is one of the essential pillars of democracy to elect the representative for ruling the country. In the election voting system, there are multiple areas such as detection of fake voters, illegal activities for fake voting, booth capturing, ballot monitoring, etc., in which Industry 4.0 can be adopted for the application of real-time monitoring, intelligent detection, enhancing security and transparency of voting and other data during the voting. According to previous research, there are no studies that have presented the significance of industry 4.0 technologies for improving the electronic voting system from a sustainability standpoint. To overcome the research gap, this study aims to present literature about Industry 4.0 technologies on the election voting system. We examined individual industry enabling technologies such as blockchain, artificial intelligence (AI), cloud computing, and the Internet of Things (IoT) that have the potential to strengthen the infrastructure of the election voting system. Based upon the analysis, the study has discussed and recommended suggestions for the future scope such as: IoT and cloud computing-based automatic systems for the detection of fake voters and updating voter attendance after the verification of the voter identity; AI-based illegal, and fake voting activities detection through vision node; blockchain-inspired system for the data integrity in between voter and election commission and robotic assistance system for guiding the voter and also for detecting disputes in the premises of election booth

How 5G wireless (and concomitant technologies) will revolutionize healthcare?

The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

Utilizing industry 4.0 on the construction site : challenges and opportunities

In recent years a step change has been seen in the rate of adoption of Industry 4.0 technologies by manufacturers and industrial organisations alike. This paper discusses the current state of the art in the adoption of industry 4.0 technologies within the construction industry. Increasing complexity in onsite construction projects coupled with the need for higher productivity is leading to increased interest in the potential use of industry 4.0 technologies. This paper discusses the relevance of the following key industry 4.0 technologies to construction: data analytics and artificial intelligence; robotics and automation; buildings information management; sensors and wearables; digital twin and industrial connectivity. Industrial connectivity is a key aspect as it ensures that all Industry 4.0 technologies are interconnected allowing the full benefits to be realized. This paper also presents a research agenda for the adoption of Industry 4.0 technologies within the construction sector; a three-phase use of intelligent assets from the point of manufacture up to after build and a four staged R&D process for the implementation of smart wearables in a digital enhanced construction site

Towards Sustainable Water Supply: Schematic Development of Big Data Collection Using Internet of Things (IoT)

Water supply systems in the United States connect raw water sources to hundreds of millions of water consumers through humongous infrastructure that include approximately one million miles of buried water mains and service connections and thousands of treatment facilities and appurtenances. This enormous set-up is currently operated by more than 170,000 public water systems. Sustainability of the water supply system faces several imminent challenges such as: 1) increasing water main breaks, 2) decreasing fresh water resources, 3) untraceable non-revenue water use, and 4) increasing water demands. However, current water supply management practices are not capable of providing fundamental solutions to the issues identified above. Big Data is a new technical concept to collect massive amounts of relevant data from sensors installed to monitor structural condition, usage, and system performance. This Big Data concept can be realized by deploying Internet of Things (IoT) technology throughout the water supply infrastructure and consumers’ usage. This paper presents a schematic development of IoT application for Big Data collection through a myriad of water clients. The scheme consists of downstream and upstream data collection using Wireless Sensor Network (WSN) technologies connecting to IoT. Downstream data shall provide water usage and performance data to clients and upstream data is similar to traditional SCADA and Automated Meter Reading (AMR) systems. Ultimately, all data will be converged to build a Big Data collection system where data mining identifies 1) local and system performances including pressure and flow, 2) non-revenue and illegitimate water consumption, and 3) locations and quantity of water breaks and water losses. The goal of this development is to enable both utilities and consumers to proactively manage their water usage and achieve higher levels of sustainability in water supply

Challenges in implementing Industry 4.0 technologies in manufacturing companies

Industry 4.0 originates from the German wording ”Industrie 4.0” and it was introduced publicly for the first time at the Hannover Fair 2011. The German government produced a report of Germany’s future actions regarding Industry 4.0 and after that, the research and buzz around the fourth Industrial revolution has been substantial. Many areas of the subject remain merely unresearched. This research will cover a service provider's perspective on the different challenges of implementing Industry 4.0 technologies. The Industry 4.0 technologies are divided into base technologies and front-end technologies as in the framework by Frank et al. (2019). The base technologies are: (1) Internet of Things, (2) Cloud, (3) Big Data and (4) Analytics. The base technologies enable the concept of Industry 4.0 and the front-end technologies. These technologies can be used for different kinds of optimization, predictive maintenance etc. The implementation of these technologies includes various challenges, which are in this research, categorized in the following way: • Managerial • Business-related • Technological The primary data for this thesis is interviews with case company X. X is a Finnish startup specializing in end-to-end IoT-systems for the manufacturing industry. They have experience from different kinds of projects such as hydro plants and heavy industry machinery. I interviewed two members of X’s board which are both experienced in their own fields of specialization. New aspects to the existing research will be achieved with a semi-structured interview. Case company X’s successful sales process usually starts from preliminary discussions and leads to a Proof of Concept (PoC). A proof of concept is the best and most common way for the implementation of their solutions, but that is usually where the problems occur¬¬ in the above-mentioned categories. Key challenges of implementation of Industry 4.0 technologies include communication, lack of a clear business case and security issues. New innovative Industry 4.0 solutions mix the digital and physical worlds and enable new business- and revenue models. The implementation process of Industry 4.0 solutions isn’t yet comprehensively researched and there are many interesting research topics for the future in all of the three categories named in this research. In addition to the named challenges, politics and legislation effect the future of Industry 4.0. Global challenges such as sustainability and labour supply can also be more thoroughly handled with the Industry 4.0 framework in the future