Development of Technological Capabilities through the Internet of Things (IoT): Survey of Opportunities and Barriers for IoT Implementation in Portugal’s Agro-Industry

The q-rung fuzzy LOPCOW-VIKOR model to assess the role of unmanned aerial vehicles for precision agriculture realization in the Agri-Food 4.0 era

Smart agriculture is gaining a lot of attention recently, owing to technological advancement and promotion of sustainable habits. Unmanned aerial vehicles (UAVs) play a crucial role in smart agriculture by aiding in different phases of agriculture. The contribution of UAVs to sustainable and precision agriculture is a critical and challenging issue to be taken into account, particularly for smallholder farmers in order to save time and money, and improve their agricultural skills. Thence, this study targets to propose an integrated group decision-making framework to determine the best agricultural UAV. Previous studies on UAV evaluation, (i) could not model uncertainty effectively, (ii) weights of experts are not methodically determined; (iii) importance of experts and criteria types are not considered during criteria weight calculation, and (iv) personalized ranking of UAVs is lacking along with consideration to dual weight entities. Herein, nine critical selection criteria are identified, drawing upon the relevant literature and experts' opinions, and five extant UAVs are considered for evaluation. To circumvent the gaps, in this work, a new integrated framework is developed considering q-rung orthopair fuzzy numbers (q-ROFNs) for apt UAV selection. Specifically, methodical estimation of experts' weights is achieved by presenting the regret measure. Further, weighted logarithmic percentage change-driven objective weighting (LOPCOW) technique is formulated for criteria weight calculation, and an algorithm for personalized ranking of UAVs is presented with visekriterijumska optimizacija i kompromisno resenje (VIKOR) approach combined with Copeland strategy. The findings show that the foremost criteria in agricultural UAV selection are "camera," "power system," and "radar system," respectively. Further, it is inferred that the most promising UAV is the DJ AGRAS T30. Since the applicability of UAV in agriculture will get inevitable, the developed framework can be an effective decision support system for farmers, managers, policymakers, and other stakeholders.

A systematic and critical review of waste management in micro, small and medium-sized enterprises: future directions for theory and practice

Waste management (WM) has received increasing attention in recent years in micro, small, and medium-sized enterprises (MSMEs). However, a comprehensive understanding of the WM research in MSMEs from different economic sectors is somehow absent in spite of its proliferation. The current review was conducted to indicate types of waste, hazards associated with waste, as well as strategies, antecedents (facilitators and barriers), and outcomes of WM in MSMEs from diverse economic sectors. The search was performed by using the Web of Science (WoS) database, which retrieves 420 articles. After excluding the papers that were not closely related to the topic, 84 articles were retained for an in-depth analysis, spanning a period of five years (from 2018 to June 2022). This review demonstrates that the types of waste generated from MSMEs include metals, plastics, chemicals, papers, wood, fabrics, stones, food, ceramics, glass, candles, and cooking oil, among others. It is also resulted that the hazards associated with waste include environmental pollution, CO2 emissions, human diseases, health disasters, and marine life destruction. Examples of the WM strategies in MSMEs research are recycling, separating, sorting, reusing, and composting waste. The findings revealed that a lack of financial resources, knowledge, experience, education, and training are some barriers encountered by MSMEs in WM. Enhancing financial performance, economic growth, competitive advantage, and sustainable development are important outcomes of WM in MSMEs. There has been a paucity of research on MSMEs WM, necessitating a thorough investigation of several issues. This research discusses implications and recommendations and presents avenues for future research. The current paper is one of the first studies to conduct a systematic review of WM in MSMEs from different economic sectors.

Enriching IoT Modules with Edge AI Functionality to Detect Water Misuse Events in a Decentralized Manner

The digital transformation of agriculture is a promising necessity for tackling the increasing nutritional needs of the population on Earth and the degradation of natural resources. Focusing on the “hot” area of natural resource preservation, the recent appearance of more efficient and cheaper microcontrollers, the advances in low-power and long-range radios, and the availability of accompanying software tools are exploited in order to monitor water consumption and to detect and report misuse events, with reduced power and network bandwidth requirements. Quite often, large quantities of water are wasted for a variety of reasons; from broken irrigation pipes to people’s negligence. To tackle this problem, the necessary design and implementation details are highlighted for an experimental water usage reporting system that exhibits Edge Artificial Intelligence (Edge AI) functionality. By combining modern technologies, such as Internet of Things (IoT), Edge Computing (EC) and Machine Learning (ML), the deployment of a compact automated detection mechanism can be easier than before, while the information that has to travel from the edges of the network to the cloud and thus the corresponding energy footprint are drastically reduced. In parallel, characteristic implementation challenges are discussed, and a first set of corresponding evaluation results is presented.

A Sustainable Productive Method for Enhancing Operational Excellence in Shop Floor Management for Industry 4.0 Using Hybrid Integration of Lean and Smart Manufacturing: An Ingenious Case Study

In industry 4.0, industry individuals implement lean and smart manufacturing to improve shop floor management systems. Shop floor management is used to control operational performance and enhance production within limited constraints. Various shop floor management approaches are used in the present scenario of industry 4.0, and mainly include value stream mapping, total productive maintenance, Internet of Things, artificial intelligence, machine learning, and fuzzy logic. The present research aims to develop an open innovation method to achieve sustainability in shop floor management systems in industry 4.0 by using lean and smart manufacturing concepts. The proposed method has been validated by an enhancement obtained in a real case of the shop floor management system in industry 4.0. The authors are confident that the proposed method would provide sustainability in the shop floor management system within limited constraints in industry 4.0.

Recent Technologies, Security Countermeasure and Ongoing Challenges of Industrial Internet of Things (IIoT): A Survey

The inherent complexities of Industrial Internet of Things (IIoT) architecture make its security and privacy issues becoming critically challenging. Numerous surveys have been published to review IoT security issues and challenges. The studies gave a general overview of IIoT security threats or a detailed analysis that explicitly focuses on specific technologies. However, recent studies fail to analyze the gap between security requirements of these technologies and their deployed countermeasure in the industry recently. Whether recent industry countermeasure is still adequate to address the security challenges of IIoT environment are questionable. This article presents a comprehensive survey of IIoT security and provides insight into today’s industry countermeasure, current research proposals and ongoing challenges. We classify IIoT technologies into the four-layer security architecture, examine the deployed countermeasure based on CIA+ security requirements, report the deficiencies of today’s countermeasure, and highlight the remaining open issues and challenges. As no single solution can fix the entire IIoT ecosystem, IIoT security architecture with a higher abstraction level using the bottom-up approach is needed. Moving towards a data-centric approach that assures data protection whenever and wherever it goes could potentially solve the challenges of industry deployment.