Equipment Vendors Research Articles

AIIMS ICU Rehabilitation (AIR): development and description of intervention for home rehabilitation of chronically ill tracheostomized patients

Background The paucity of state-supported rehabilitation for chronically ill patients with long-term tracheostomies has ramifications of prolonged hospital-stay, increased burden on acute-care resources, and nosocomial infections. Few interventions describe home rehabilitation of adult tracheostomized patients. Almost none involve stakeholders. This paper describes the All-India Institute of Medical Sciences (AIIMS) ICU rehabilitation (AIR) healthcare intervention developed to facilitate home rehabilitation of chronically ill tracheostomized patients. Methods The AIR intervention development was based on the experience-based codesign theory (EBCD). A core research-committee studied prevalent knowledge and gaps in the area. Patients-carer and health-care stakeholders’ experiences of barriers and facilitators to home care resulted in an intervention with interlinked components: family-carer training, equipment bank, m-health application, and follow-up, guided by the Medical Research Council (MRC) framework. Healthcare stakeholders (doctors, nurses, medical equipment vendors) and patient-carer dyads were engaged to gather experiences at various stages to form smaller codesign teams for each component. Multiple codesign meetings iteratively allowed refinement of the intervention over one year. The Template for Intervention Description and Replication (TIDieR) checklist was used to report the AIR intervention. Results The first component comprised a minimum of three bedside hands-on training sessions for carers relating to tracheostomy suction, catheter care, monitoring oxygenation, enteral feeding, skincare, and physiotherapy, buttressed by pictorial-books and videos embedded in a mobile-application. The second was an equipment-bank involving a rental-retrieval model. The third component was a novel m-health tool for two-way communication with the core group and community of other patient-carers in the project for follow-up and troubleshooting. Home visits on days 7 and 21 post-discharge assessed patient hygiene, nutrition, physiotherapy, and established contact with the nearest primary healthcare facility for the future. Conclusions Findings support the EBCD-based development using active feedback from stakeholders. Assessment of feasibility, process and effectiveness evaluation will follow.

Utilisation of the site assessment energy indices for aquaculture in exposed waters: biology, technology, operations and maintenance

When moving from a very sheltered aquaculture site to a very exposed oceanic aquaculture site, the energy increases proportionally in a continuum. Lojek et al. (in review) considered the primary influential parameters (water current, wave height, wave period, wavelength and water depth) which influence the species, structure, technology, methods, and operational aspects of any aquaculture endeavour and investigated six possible indices which cover these variables. Added to advanced computer modelling, assisted by detailed and constant environmental monitoring, it may be possible to refine site selection, structure selection and design, species selection, equipment and logistic requirements and health and safety requirements. This manuscript has selected two indicative indices: Specific Exposure Energy (SEE) index and Exposure Velocity (EV) index from the potential equations provided by Lojek et al. (in review) and compared them with known operational aquaculture sites highlighting present structural capability and limitations. The two indices are also utilized to reflect on their suitability for assessing sample sites with respect to biological, technological, operational or maintenance aspects of aquaculture activities. The indices have shown themselves to be useful tools in the general assessment of the energy that will influence the species and structure selection at potential aquaculture sites. This information can help prospective fish farmers characterize their sites concisely and accurately to consultants, regulators, equipment vendors, and insurance brokers.

Improving efficiency and quality of operational industrial production assets information management in customer–vendor interaction

Industrial assets management has a key role in ensuring continuity of industrial production via purchasing, warehousing and maintenance of devices and spare parts used in manufacturing, but it suffers from data and information accessibility, completeness, consistency, interoperability, and timeliness challenges in the customer - equipment vendors interaction and information sharing. Current practices in devices and spare parts purchasing, warehousing and maintenance include a lot of manual information search, validation and update work done at the manufacturing companies to maintain high quality master data records for the production assets management. This article addresses the challenge of improving efficiency and quality of operational production assets information management in industry customer company interaction with their production equipment vendors, with a design science research approach. The research was executed in collaboration between research organizations, forest industry companies, industrial production equipment vendors and information technology (IT) companies on two parallel and complementary research tracks, which are described with their key research results. The contributions are an ex-ante evaluated digital marketplace concept with preliminary requirements, and an ex-post evaluated semi-automated master data harmonization tool, as artefacts for improving efficiency and quality of production assets information management in industrial customer–vendors interaction. As theoretical contribution, the article provides a synthesis of the research results in the framework of information systems (IS) design theory as a nascent and novel design theory on designing IS artifacts for improving efficiency and quality of production assets information management, both in single industrial customer company and ecosystem settings. The contributions provide a starting point for further research and development of a digital marketplace for improving production assets information management in industrial customers – vendors interaction, potentially also applicable for similar ecosystems in other continuous production process -based manufacturing industries.

AIIMS ICU Rehabilitation (AIR): development and description of intervention for home rehabilitation of chronically ill tracheostomized patients

Background The paucity of state-supported rehabilitation for chronically ill patients with long-term tracheostomies has ramifications of prolonged hospital-stay, increased burden on acute-care resources, and nosocomial infections. Few interventions describe home rehabilitation of adult tracheostomized patients. Almost none involve stakeholders. This paper describes the All-India Institute of Medical Sciences (AIIMS) ICU rehabilitation (AIR) healthcare intervention developed to facilitate home rehabilitation of chronically ill tracheostomized patients. Methods The AIR intervention development was based on the experience-based codesign theory (EBCD). A core research-committee studied prevalent knowledge and gaps in the area. Patients-carer and health-care stakeholders’ experiences of barriers and facilitators to home care resulted in an intervention with interlinked components: family-carer training, equipment bank, m-health application, and follow-up, guided by the Medical Research Council (MRC) framework. Healthcare stakeholders (doctors, nurses, medical equipment vendors) and patient-carer dyads were engaged to gather experiences at various stages to form smaller codesign teams for each component. Multiple codesign meetings iteratively allowed refinement of the intervention over one year. The Template for Intervention Description and Replication (TIDieR) checklist was used to report the AIR intervention. Results The first component comprised a minimum of three bedside hands-on training sessions for carers relating to tracheostomy suction, catheter care, monitoring oxygenation, enteral feeding, skincare, and physiotherapy, buttressed by pictorial-books and videos embedded in a mobile-application. The second was an equipment-bank involving a rental-retrieval model. The third component was a novel m-health tool for two-way communication with the core group and community of other patient-carers in the project for follow-up and troubleshooting. Home visits on days 7 and 21 post-discharge assessed patient hygiene, nutrition, physiotherapy, and established contact with the nearest primary healthcare facility for the future. Conclusions Findings support the EBCD-based development using active feedback from stakeholders. Assessment of feasibility, process and effectiveness evaluation will follow.

Cost analysis of hydrogen production by high-temperature solid oxide electrolysis

We estimate construction and operation costs of gigawatt-scale solid oxide electrolysis (SOE) facilities for producing high purity hydrogen gas from water. Manufacturing and assembly costs for two types of SOE cell stacks are estimated using a detailed design for manufacture and assembly (DFMA®) analysis. Modular balance of plant (BOP) process equipment is designed and sized with Aspen®, and cost estimated using equipment vendor quotes. Factory and on-site assembly and installation costs for SOEC stack and BOP equipment integration into modular SOE process units are calculated using a simplified DFMA® method. Total stack costs on a stack input power (SIP) basis reduce to <$100/kWe DCSIP for >500 MWe DCSIP/year production rates with electrode cermet, interconnects, and high-temperature heat treatments dominating the total cost. Integration of stacks with larger BOP equipment operating at higher pressures offers ∼36% cost reduction in total facility capital cost due to an economies of physical scale effect since BOP equipment comprises >50% of facility costs. Optimized H2 prices decrease from ∼$4/kgH2 to ∼$2/kgH2 for 1 GWe DCSIP facilities using $0.025/kWh electricity price. All costs are reported in 2021 US dollars.

Designing price-service menus in a product-service system

We study contract menu design by a vendor leasing production equipment to its clients who serve customers. The equipment can fail which can cause delays to clients' customers. The equipment vendor can offer its clients three types of lease-and-repair contracts: equipment lease with an immediate replacement upon failure, repair with a redundant unit on client premises (parallel layout), and repair without a backup unit on the premises. The vendor does not have full information about each client but knows that clients fall into two types. ‘High’ (vs. ‘Low’) type clients have a higher (vs. lower) willingness to pay but have customers who are more (vs. less) delay-sensitive. Modeling the interaction between the vendor and its clients as a leader-follower game and using queueing theory, we show that a monopolistic vendor can increase its expected profit through second-degree price discrimination by offering a menu of contracts to its clients. We find that when the distribution of customers with low and high willingness to pay is not skewed (one-sided) and either the cost of repair or cost of equipment is low the vendor can increase its profit by inducing price discrimination through offering the menus proposed in the paper.

AIIMS ICU Rehabilitation (AIR): development and description of intervention for home rehabilitation of chronically ill tracheostomized patients.

The paucity of state-supported rehabilitation for chronically ill patients with long-term tracheostomies has ramifications of prolonged hospital-stay, increased burden on acute-care resources, and nosocomial infections. Few interventions describe home rehabilitation of adult tracheostomized patients. Almost none involve stakeholders. This paper describes the All-India Institute of Medical Sciences (AIIMS) ICU rehabilitation (AIR) healthcare intervention developed to facilitate home rehabilitation of chronically ill tracheostomized patients. The AIR intervention development was based on the experience-based codesign theory (EBCD). A core research-committee studied prevalent knowledge and gaps in the area. Patients-carer and health-care stakeholders' experiences of barriers and facilitators to home care resulted in an intervention with interlinked components: family-carer training, equipment bank, m-health application, and follow-up, guided by the Medical Research Council (MRC) framework. Healthcare stakeholders (doctors, nurses, medical equipment vendors) and patient-carer dyads were engaged to gather experiences at various stages to form smaller codesign teams for each component. Multiple codesign meetings iteratively allowed refinement of the intervention over one year. The Template for Intervention Description and Replication (TIDieR) checklist was used to report the AIR intervention. The first component comprised a minimum of three bedside hands-on training sessions for carers relating to tracheostomy suction, catheter care, monitoring oxygenation, enteral feeding, skincare, and physiotherapy, buttressed by pictorial-books and videos embedded in a mobile-application. The second was an equipment-bank involving a rental-retrieval model. The third component was a novel m-health tool for two-way communication with the core group and community of other patient-carers in the project for follow-up and troubleshooting. Home visits on days 7 and 21 post-discharge assessed patient hygiene, nutrition, physiotherapy, and established contact with the nearest primary healthcare facility for the future. Findings support the EBCD-based development using active feedback from stakeholders. Assessment of feasibility, process and effectiveness evaluation will follow.

Implementation of Decision-Making Algorithms and Key Requirement Approach for Vendor Selection in Telecommunication Device Bidding

The influence of perceived quality is a classic problem in a vendor selection process. To overcome this problem, many algorithms have been used in decision making. In this paper we have carried out the identification of planning team needs and the optimization of the bidding scheme using key requirements to minimize the influence of quality perceptions. The Kano Model Analysis method, the Analytical Hierarchy Process and Technique for Order Preference by Similarity to the Ideal Solution are used to analyze and determine the key requirements in the bidding process for telecommunications equipment needed by the planning team. Vendor selection based on key of requirements specifications is carried out in six stages, namely the preparation stage, requirements search, selection of Key of Requirements specifications, vendor selection, accuracy testing and conclusions. The results of the analysis show that the need for new planning and architecture of telecommunication service providers can increase to NFVi and services. An important criterion for NVFi (Hardware) development is Virtual Infrastructure Management (VIM) with a weight of 22%, while the service criteria are Fixed Services with a weight of 50.94%. Based on the analysis results, the preference value of each telecommunication equipment vendor (supplier) is also obtained.

Multi-vendor evaluation of artificial intelligence as an independent reader for double reading in breast cancer screening on 275,900 mammograms

BackgroundDouble reading (DR) in screening mammography increases cancer detection and lowers recall rates, but has sustainability challenges due to workforce shortages. Artificial intelligence (AI) as an independent reader (IR) in DR may provide a cost-effective solution with the potential to improve screening performance. Evidence for AI to generalise across different patient populations, screening programmes and equipment vendors, however, is still lacking.MethodsThis retrospective study simulated DR with AI as an IR, using data representative of real-world deployments (275,900 cases, 177,882 participants) from four mammography equipment vendors, seven screening sites, and two countries. Non-inferiority and superiority were assessed for relevant screening metrics.ResultsDR with AI, compared with human DR, showed at least non-inferior recall rate, cancer detection rate, sensitivity, specificity and positive predictive value (PPV) for each mammography vendor and site, and superior recall rate, specificity, and PPV for some. The simulation indicates that using AI would have increased arbitration rate (3.3% to 12.3%), but could have reduced human workload by 30.0% to 44.8%.ConclusionsAI has potential as an IR in the DR workflow across different screening programmes, mammography equipment and geographies, substantially reducing human reader workload while maintaining or improving standard of care.Trial registrationISRCTN18056078 (20/03/2019; retrospectively registered).

Sport-Strides (Sports Learning and Event System)

Sport-Strides is a pioneering initiative that aims to tackle the challenge of insufficient information and resources pertaining to various sports. The project strives to create a unified platform that brings together institutions, academies, and equipment vendors to provide a business-to-customer service experience. Through this platform, users can explore diverse sports and areas of interest, identify nearby training institutes and academies, and access resources related to upcoming events. One of the key highlights of this platform is its provision of external links related to upcoming events for different sports, thereby enabling users to stay up-to-date with the latest happenings. The platform offers a win-win situation for vendors, as they can attract new consumers referred from the platform. Additionally, the project aims to help training institutes get discovered by more users looking for a professional training space. Problem Statement: As a Newbie, there is currently no resource accessible to learn about a certain sport, including how it is played, its rules, where to receive professional training for the sport, and where to find the equipment needed for the activity. lack of knowledge about events at the local, national, and international levels for the specific sport.

Development of a Platform for Distributed Energy Resources Management on the Basis of a Digital Twin

The paper discusses the development of a platform for distributed energy resources management based on digital twins. The platform use cases include demand response, electric vehicle charging, peer-to-peer energy trading, storage scheduling, virtual power plant, and so on. Thanks to the digital twin, the platform can perform the use cases controlling either real operation-stage equipment or virtual design-stage simulation models. The platform offers mass distributed energy resources owners and operators to improve the power supply quality (including stability), reduce costs (including transaction overhead), and gain emerging market opportunities (including participation in various aggregators' programs). Software and equipment vendors are interested in the platform's capability to quickly assemble distributed energy management systems almost without programming. The digital twin and the platform are designed with the viewpoint-based approach established by the international systems engineering standard ISO/IEC/IEEE 42010. The typical power system digital twin architecture is described. The major kinds of mathematical models as part of digital twins are presented: physical models based on numerical solutions of differential equations and optimization problems, machine learning models, knowledge-based models. The interoperability of such heterogeneous models is ensured on the basis of the ontological model of distributed energy. The platform architecture is represented from three key viewpoints: functional, information, and software. To formalize and ultimately automate the integration of heterogeneous models, we propose novel mathematical methods of model-based system engineering based on category theory, including universal constructions and the multicomma. The multicomma category is shown to be constructed using standard product, exponent, and pushout constructions, which makes it possible to establish a number of its practically significant properties.

Unlocking the Path toward Intelligent Telecom Marketplaces for Beyond 5G and 6G Networks

6G systems are perceived to be heavily softwarised, and therefore, the collaboration among all stakeholders, such as network and cloud providers, operators, application developers, service providers and device and equipment vendors, shall occur via software in a secured, distributed, and automated manner. This could be envisioned with a brokerless and immutable Marketplace anchored in Distributed Ledger Technologies, removing the need for a trusted party as Marketplace operator while avoiding this single point of failure, increasing transparency and flexibility of operational rules, and featuring automated contract negotiation and fulfillment supporting governance, delivery, and billing operations. This work goes a step forward and introduces a Smart Resource and Service Discovery application, based on intent recognition and Machine Learning assisted techniques, to enable the automated discovery of resources and services exposed over the Marketplace. Evaluation results demonstrate the accuracy of our approach and its suitability to provide decentralized Telecom Marketplaces with intelligent and datadriven discovery capabilities.

Deregulated Distribution System Planning - Incremental Capacity Auction Mechanism With Transactive DERs

High penetrations of distributed energy resources (DERs) are driving the transformation of traditional distribution networks into transactive energy distribution systems (TEDS). TEDS depart from conventional distribution system constructs to 1) enable a local distribution operator to maximize social welfare, 2) enable peer-to-peer energy transactions, 3) extract maximum participation and benefits from DERs, 4) usher in competition in the distribution sector to supply electricity via DERs, and 5) hold the potential for a lower asset cost solution, greater customer choice, and higher reliability. The conventional distribution system planning is inadequate for this purpose. Following the new TEDS paradigm, an incremental capacity auction (ICA) is proposed in this paper considering: 1) bids for power capacity from all energy sources (DERs and transmission), 2) bids for network asset upgrades from equipment vendors, and 3) bids from new loads. A holistic auction settlement procedure is developed for the proposed ICA mechanism that can concurrently determine the optimal power capacity to be procured and network asset upgrading, while maximizing social welfare. Further, locational marginal price for power capacity demand is estimated as a by-product of the ICA solution. Benefits are demonstrated via case studies and include increased participation of DERs to supply energy, maximizing the social welfare, and enabling assets deferral considering the available local resources.

In-depth study of RNTI management in mobile networks: Allocation strategies and implications on data trace analysis

The advance of mobile network technologies and components heavily relies on data-driven techniques. This is especially true for fifth generation (5G) and the upcoming sixth generation (6G) networks, as the optimization of network components and protocols is expected to be fueled by artificial intelligence (AI) based solutions. When using real-world radio access measurement traces, the identity of individual users is not directly accessible because at runtime operation Base Stations (BSs) assign Radio Network Temporary Identifiers (RNTIs) to users. RNTIs are not bound to a user but are reused upon expiration of an inactivity timer, whose duration is operator dependent. This implies that, over time, multiple users are mapped to the same RNTI. In fact, the allocation of RNTIs to users is implemented in diverse and proprietary ways by operators and equipment vendors. Distinguishing individual users within the RNTI space is a non-trivial task and key to analyze traffic traces properly. In this paper, we make the following contributions: (i) we propose and validate two complementary methodologies to identify the RNTI inactivity threshold, and we characterize (ii) the RNTI allocation process of network operators, and (iii) the user traffic patterns given the specific RNTI allocation process. Our study is based on a large dataset we collected from production BSs of several mobile network operators across five different countries. We find that there exist heterogeneous strategies for RNTI allocation that BSs dynamically use depending on the traffic load and daytime. We further observe that the RNTI expiration threshold is in the order of minutes, and demonstrate how using thresholds around 10 s, as in the vast majority of the literature, can bias subsequent analyses. Overall, our work provides an important step towards dependable mobile network trace analysis, and lays solid foundations to research relying on traffic traces for data-driven analysis.

Variations in size-specific effective dose with patient stature and beam width for kV cone beam CT imaging in radiotherapy

The facilities now available on linear accelerators for external beam radiotherapy enable radiation fields to be conformed to the shapes of tumours with a high level of precision. However, in order for the treatment delivered to take advantage of this, the patient must be positioned on the couch with the same degree of accuracy. Kilovoltage cone beam computed tomography systems are now incorporated into radiotherapy linear accelerators to allow imaging to be performed at the time of treatment, and image-guided radiation therapy is now standard in most radiotherapy departments throughout the world. However, because doses from imaging are much lower than therapy doses, less effort has been put into optimising radiological protection of imaging protocols. Standard imaging protocols supplied by the equipment vendor are often used with little adaptation to the stature of individual patients, and exposure factors and field sizes are frequently larger than necessary. In this study, the impact of using standard protocols for imaging anatomical phantoms of varying size from a library of 193 adult phantoms has been evaluated. Monte Carlo simulations were used to calculate doses for organs and tissues for each phantom, and results combined in terms of size-specific effective dose (SED). Values of SED from pelvic scans ranged from 11 mSv to 22 mSv for male phantoms and 8 mSv to 18 mSv for female phantoms, and for chest scans from 3.8 mSv to 7.6 mSv for male phantoms and 4.6 mSv to 9.5 mSv for female phantoms. Analysis of the results showed that if the same exposure parameters and field sizes are used, a person who is 5 cm shorter will receive a size SED that is 3%–10% greater, while a person who is 10 kg lighter will receive a dose that is 10%–14% greater compared with the average size.

Landing AI on Networks: An Equipment Vendor Viewpoint on Autonomous Driving Networks

The tremendous achievements of Artificial Intelligence (AI) in computer vision, natural language processing, games and robotics, has extended the reach of the AI hype to other fields: in telecommunication networks, the long term vision is to let AI fully manage, and autonomously drive, all aspects of network operation. In this industry vision paper, we discuss challenges and opportunities of Autonomous Driving Network (ADN) driven by AI technologies. To understand how AI can be successfully landed in current and future networks, we start by outlining challenges that are specific to the networking domain, putting them in perspective with advances that AI has achieved in other fields. We then present a system view, clarifying how AI can be fitted in the network architecture. We finally discuss current achievements as well as future promises of AI in networks, mentioning a roadmap to avoid bumps in the road that leads to true large-scale deployment of AI technologies in networks.

Operations, risk, and small firms: Field results from irrigation equipment vendors in Senegal

What are supply chain management challenges in a lower‐income economy, and how do managers at smaller firms address them? This field study presents these challenges from the perspective of the 60 managers who run firms selling irrigation equipment in Senegal. By canvasing 35 cities, we gain unique visibility into how private supply chains, on which public officials and smallholder farmers in Africa rely, effectively deliver agricultural goods. The primary challenges for managers in this supply chain are day‐to‐day risks that are quality and contractual in nature and have financial implications. City size in combination with supplier type, firm size, and manager network determine risk exposure. Firms’ efforts to manage the chain are more reactive than proactive and more informal than formal, which reveals an opportunity for public agencies to support supplier and customer coordination. Public decision makers should tailor support to account for the differential risks that city size brings to supply chain management. This support should include not just financing the firms directly but should also entail giving loans to customers, certifying suppliers, and sharing inventory risk with public and nonprofit partners.

Innovative Individual Vehicle Record Traffic Data Quality Analysis Methods

Most traffic data collection sites have individual vehicle record (IVR) data of each vehicle passing the sensor area but have traditionally only stored binned and summary data because of previous hardware data storage limitations. Most recently, agencies and traffic equipment vendors are trending more toward IVR data-capable sites. Detailed IVR traffic data (including weigh-in-motion) are being collected, processed, and provided as an output product to agencies. Agencies process and store this very detailed IVR data from both portable and/or permanent traffic counting locations and could benefit from enhanced tools and methods that best leverage this rich information. This research paper details an extensive IVR literature review and 10 unique IVR innovative quality control and processing methods that would not be possible with traditional binned or summary speed, classification, and/or weight data. By employing these innovative methods, agencies are now better able to troubleshoot and check their data. These methods also offer improved monitoring of IVR sites to better assist the field staff who perform site visits, troubleshoot sensors, and fix equipment issues. The more detailed IVR data are best suited to meeting several customer needs and provide the same data streams that already exist from binned data sources. IVR data also provide additional value to every data collection site through more detailed traffic data that better explain travel characteristics.

Assessing the Barriers Towards the Glocalization of India’s Mobile Industry: An IVIFs-DEMATEL with Choquet Integral Method

Although mobile brands from various countries have taken to the global market, some brands are left to be GLOCALised (local to global). The nonGLOCALisation of these brands are due to some unseen hindrances. This paper is unique in its aim to analyze the challenges faced by local mobile phone supply chains (MPSC) from entering the global market in an Indian context. We analyze the barriers’ entry by combining the IVIFs-DEMATEL method with Choquet Integral; also, we compare the obtained results to those from the IVIFs-DEMATEL methodology. The differentiated analysis reveals that ‘Equipment Vendor Restrictions’ and ‘Lack of Awareness about Reverse Logistics’ are the main hindrances preventing local manufacturers from reaching the global space. Furthermore, the findings of this study suggest that ‘Carrier Aggregation Complexity’, ‘Equipment Vendor Restrictions’, and ‘Challenge to Recycling of Plastics’ are vital factors nonconducive towards the smooth working of local mobile makers across the country. The results can help domestic policymakers to improve their decision-making while trying to find ways for the globalization of the mobile phone sector.

Role and challenge of technology toward a smart sustainable city: Topic modeling, classification, and time series analysis using information and communication technology patent data

This research defines and classifies essential technology groups that comprise a smart sustainable city (SSC) and explores patterns of technological growth by analyzing patents. First, topic modeling and network analysis are conducted using patent text data and international patent classification code, respectively. Patents are classified and defined based on the technology theme and the type of technology provider. Second, hardware-oriented and service application-oriented technologies are classified and predicted using machine learning. Third, the similarities in growth patterns of different technology groups are explored using dynamic time warping (DTW). Moreover, lagging or preceding relationships are examined using multivariate time series analysis. Network infrastructure and Internet-of-things (IoT) application technologies have short-term lagging and preceding relationships along with long-term equilibrium relationships. In terms of player groups, long-term relationships between device vendors, chipset makers, network operator and IoT service provider, and network equipment vendors are confirmed. Technologies for realizing a sustainable city must be prioritized, and the strategic direction of technology must be established to realize truly smart sustainable cities. The supplier of technologies along with possible collaboration opportunities must also be selected. This study proposes the role and direction of technology for SSC and presents a comprehensive methodology for analyzing technology using patents.