Ningbo Easy Connect Telecommunication Equipment Co Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Introduction

The Mobile phone activity dataset is composed by one week of Call Details Records (CDRs) from the city of Milan and the Province of Trentino (Italy).

Description of the dataset

Every time a user engages a telecommunication interaction, a Radio Base Station (RBS) is assigned by the operator and delivers the communication through the network. Then, a new CDR is created recording the time of the interaction and the RBS which handled it. The following activities are present in the dataset:

• received SMS
• sent SMS
• incoming calls
• outgoing calls
• Internet activity

In particular, Internet activity is generated each time a user starts an Internet connection or ends an Internet connection. Moreover, during the same connection a CDR is generated if the connection lasts for more than 15 min or the user transferred more than 5 MB.

The datasets is spatially aggregated in a square cells grid. The area of Milan is composed of a grid overlay of 1,000 (squares with size of about 235×235 meters. This grid is projected with the WGS84 (EPSG:4326) standard. For more details we link the original paper http://go.nature.com/2fcOX5E

The data provides CellID, CountryCode and all the aforementioned telecommunication activities aggregated every 60 minutes.

Original datasource

The Mobile phone activity dataset is a part of the Telecom Italia Big Data Challenge 2014, which is a rich and open multi-source aggregation of telecommunications, weather, news, social networks and electricity data from the city of Milan and the Province of Trentino (Italy). The original dataset has been created by Telecom Italia in association with EIT ICT Labs, SpazioDati, MIT Media Lab, Northeastern University, Polytechnic University of Milan, Fondazione Bruno Kessler, University of Trento and Trento RISE. In order to make it easy-to-use, here we provide a subset of telecommunications data that allows researchers to design algorithms able to exploit an enormous number of behavioral and social indicators. The complete version of the dataset is available at the following link: http://go.nature.com/2fz4AFr

Relevant, external, data sources

The presented datasets can be enriched by using census data provided by the Italian National Institute of Statistics (ISTAT) (http://www.istat.it/en/), a public research organization and the main provider of official statistics in Italy. The census data have been released for 1999, 2001 and 2011. The dataset (http://www.istat.it/it/archivio/104317), released in Italian, is composed of four parts: Territorial Bases (Basi Territoriali), Administrative Boundaries (Confini Amministrativi), Census Variables (Variabili Censuarie) and data about Toponymy (Dati Toponomastici).

Motivational video: https://www.youtube.com/watch?v=_d2_RWMsUKc

Relevant papers

Blondel, Vincent D., Adeline Decuyper, and Gautier Krings. "A survey of results on mobile phone datasets analysis." EPJ Data Science 4, no. 1 (2015): 1.

Francesco Calabrese, Laura Ferrari, and Vincent D. Blondel. 2014. Urban Sensing Using Mobile Phone Network Data: A Survey of Research. ACM Comput. Surv. 47, 2, Article 25 (November 2014), 20 pages.

Eagle, Nathan, Michael Macy, and Rob Claxton. "Network diversity and economic development." Science 328, no. 5981 (2010): 1029-1031.

Lenormand, Maxime, Miguel Picornell, Oliva G. Cantú-Ros, Thomas Louail, Ricardo Herranz, Marc Barthelemy, Enrique Frías-Martínez, Maxi San Miguel, and José J. Ramasco. "Comparing and modelling land use organization in cities." Royal Society open science 2, no. 12 (2015): 150449.

Louail, Thomas, Maxime Lenormand, Oliva G. Cantu Ros, Miguel Picornell, Ricardo Herranz, Enrique Frias-Martinez, José J. Ramasco, and Marc Barthelemy. "From mobile phone data to the spatial structure of cities." Scientific reports 4 (2014).

De Nadai, Marco, Jacopo Staiano, Roberto Larcher, Nicu Sebe, Daniele Quercia, and Bruno Lepri. "The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective." WWW, 2016.

Citation

We kindly ask people who use this dataset to cite the following paper, where this aggregation comes from:

Barlacchi, Gianni, Marco De Nadai, Roberto Larcher, Antonio Casella, Cristiana Chitic, Giovanni Torrisi, Fabrizio Antonelli, Alessandro Vespignani, Alex Pentland, and Bruno Lepri. "A multi-source dataset of urban life in the city of Milan and the Province of Trentino." Scientific data 2 (2015).

It turns ArcGIS into a system for communications organizations to easily inventory their assets and keep information up to date. It provides simple to use interactive system maps and dashboards for office and field staff, and increases collaboration.

After deploying, organizations with no digital communication data can immediately begin mapping their systems using GPS or digitizing data with web or desktop software. Organizations with existing spatial data can load it and begin using the apps.

Learn More

If you found the dataset useful, your upvote will help others discover it. Thanks for your support!

This dataset simulates customer behavior for a fictional telecommunications company. It contains demographic information, account details, services subscribed to, and whether the customer ultimately churned (stopped using the service) or not. The data is synthetically generated but designed to reflect realistic patterns often found in telecom churn scenarios.

Purpose:

The primary goal of this dataset is to provide a clean and straightforward resource for beginners learning about:

• Exploratory Data Analysis (EDA): Understanding customer characteristics and identifying potential drivers of churn through visualization and statistical summaries.
• Data Preprocessing: Handling categorical features (like converting text to numbers) and scaling numerical features.
• Classification Modeling: Building and evaluating simple machine learning models (like Logistic Regression or Decision Trees) to predict customer churn.

Features:

The dataset includes the following columns:

• CustomerID: Unique identifier for each customer.
• Age: Customer's age in years.
• Gender: Customer's gender (Male/Female).
• Location: General location of the customer (e.g., New York, Los Angeles).
• SubscriptionDurationMonths: How many months the customer has been subscribed.
• MonthlyCharges: The amount the customer is charged each month.
• TotalCharges: The total amount the customer has been charged over their subscription period.
• ContractType: The type of contract the customer has (Month-to-month, One year, Two year).
• PaymentMethod: How the customer pays their bill (e.g., Electronic check, Credit card).
• OnlineSecurity: Whether the customer has online security service (Yes, No, No internet service).
• TechSupport: Whether the customer has tech support service (Yes, No, No internet service).
• StreamingTV: Whether the customer has TV streaming service (Yes, No, No internet service).
• StreamingMovies: Whether the customer has movie streaming service (Yes, No, No internet service).
• Churn: (Target Variable) Whether the customer churned (1 = Yes, 0 = No).

Data Quality:

This dataset is intentionally clean with no missing values, making it easy for beginners to focus on analysis and modeling concepts without complex data cleaning steps.

Inspiration:

Understanding customer churn is crucial for many businesses. This dataset provides a sandbox environment to practice the fundamental techniques used in churn analysis and prediction.

Original datasource The Mobile phone activity dataset is a part of the Telecom Italia Big Data Challenge 2014, which is a rich and open multi-source aggregation of telecommunications, weather, news, social networks and electricity data from the city of Milan and the Province of Trentino (Italy). The original dataset has been created by Telecom Italia in association with EIT ICT Labs, SpazioDati, MIT Media Lab, Northeastern University, Polytechnic University of Milan, Fondazione Bruno Kessler, University of Trento and Trento RISE. In order to make it easy-to-use, here we provide a subset of telecommunications data that allows researchers to design algorithms able to exploit an enormous number of behavioral and social indicators. The complete version of the dataset is available at the following link: http://go.nature.com/2fz4AFr We kindly ask people who use this dataset to cite the following paper, where this aggregation comes from: Citation Barlacchi, Gianni, Marco De Nadai, Roberto Larcher, Antonio Casella, Cristiana Chitic, Giovanni Torrisi, Fabrizio Antonelli, Alessandro Vespignani, Alex Pentland, and Bruno Lepri. "A multi-source dataset of urban life in the city of Milan and the Province of Trentino." Scientific data 2 (2015).

The containerized and modular data center market is experiencing robust growth, projected to reach $14.46 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 18.49% from 2025 to 2033. This expansion is driven by several key factors. The increasing demand for edge computing necessitates deploying data centers closer to data sources, making modular and containerized solutions ideal due to their rapid deployment and scalability. Furthermore, the rising need for flexible and adaptable IT infrastructure, particularly in sectors like telecommunications and cloud computing, fuels market growth. Organizations are seeking cost-effective solutions that can be easily expanded or relocated as needed, aligning perfectly with the attributes of these data center types. Finally, prefabricated components and standardized designs reduce construction time and costs, further contributing to the market's attractiveness. Competition is fierce, with established players like Hewlett Packard Enterprise, IBM, Dell, Cisco, Huawei, and Emerson Network Power dominating the market alongside other significant contributors like Schneider Electric and Rittal. However, the market also presents opportunities for smaller, specialized companies offering innovative solutions and niche services. While the market faces challenges such as high initial investment costs and potential limitations in terms of power capacity and cooling efficiency in certain deployments, ongoing technological advancements and evolving industry best practices are mitigating these concerns. The market’s future trajectory hinges on continued technological innovation, particularly in areas such as energy efficiency, improved cooling systems, and enhanced security features, as these elements will play a crucial role in driving further adoption and influencing market segmentation. Recent developments include: September 2022: Vertiv introduced Vertiv prefabricated modular data centers and infrastructure options in India. The integrated solutions are flexible platforms suited for IT asset deployment and provide a straightforward way to install capacity in less time. They also offer simple scalability, letting the data center operator start with a solution that suits immediate needs and then scale up as needed. They incorporate elements from Vertiv's solution portfolio, such as the modular and scalable Vertiv Liebert EXM UPS power protection, row-based Vertiv Liebert CRV thermal management units with intelligent Vertiv Liebert iCOMTM controls, Vertiv VR racks, and Vertiv's rack power distribution units., June 2022: Schneider Electric announced the debut of a faster-prefabricated data center solution in Europe and a "modernization" of its infrastructure management tool, Ecostruxure IT. Under the "Easy Modular Data Center All-in-One" brand, Schneider will deliver prefabricated containerized data centers ranging from 27kW to 80kW manufactured at its Barcelona factory, with a simplified ordering process. Containers can now be bought through a simple catalog and delivered in as little as 12 weeks.. Key drivers for this market are: Need for Portability and Increasing Demand for Scalable Data Center Solutions, Rising Demand for Energy Efficient Data Centers. Potential restraints include: Need for Portability and Increasing Demand for Scalable Data Center Solutions, Rising Demand for Energy Efficient Data Centers. Notable trends are: Rising Demand for Energy Efficient Data Centers.

About the dataset

The telecommunications dataset for predicting customer churn. This is a historical customer dataset where each row represents one customer. The data is relatively easy to understand, and you may uncover insights you can use immediately. Typically it is less expensive to keep customers than acquire new ones, so the focus of this analysis is to predict the customers who will stay with the company.

This data set provides information to help you predict what behavior will help you to retain customers. You can analyze all relevant customer data and develop focused customer retention programs.

The dataset includes information about:

• Customers who left within the last month – the column is called Churn
• Services that each customer has signed up for – phone, multiple lines, internet, online security, online backup, device protection, tech support, and streaming TV and movies
• Customer account information – how long they had been a customer, contract, payment method, paperless billing, monthly charges, and total charges
• Demographic info about customers – gender, age range, and if they have partners and dependents

telecommunications — protection against obstacles

Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries

The size of the Ireland Data Center Networking market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 16.30% during the forecast period.Data center networking is about the infrastructure connecting various aspects of a data center with each other to facilitate easy communication and movement of data. It involves such network devices as switches, routers, firewalls, and all other equipment facilitating information communication between servers, storage systems, or other IT equipment.Ireland Data Center Networking Market, therefore, grows steadily since the need for data centers is continually growing within that country. Recently, Ireland emerged as one of the favorite destinations for a data center, owing to its better business climate and strong infrastructural back-end and abundant access to renewable energy.The market is characterized by such advanced networking technologies as high-speed fiber optics, SDN, and network virtualization. All these help to manage the increasing volume of data traffic, improve performance, and increase operational efficiency in the data centers. Recent developments include: March 2023: Arista Networks unveiled the Arista WAN Routing System, a groundbreaking solution that unifies three distinct networking components: enterprise-grade routing platforms, carrier and cloud-agnostic internet transit features, and the innovative CloudVision® Pathfinder Service, designed to streamline and enhance customer-wide area networks., October 2022: Kyndryl introduced an innovative, fully integrated hybrid cloud solution in partnership with Dell Technologies and Microsoft Corporation. This comprehensive solution empowers clients operating within data centers, remote locations, and mainframe environments to expedite their cloud transformation initiatives significantly. Clients can bolster their cloud transformation efforts by leveraging Dell infrastructure, Kyndryl's managed services, and the extensive capabilities of Microsoft Azure.. Key drivers for this market are: Increasing Utilization of Cloud Storage is Driving the Market Growth, Rising Need for Backup and Storage is Expanding the Market Demand. Potential restraints include: Lack of Skilled Professionals is Hindering the Market Demand. Notable trends are: IT & Telecommunication Segment to Hold Major Share in the Market.

Albania Postal Services: Number of Simple Letters and Parcels data was reported at 15,126.000 Unit th in 2017. This records an increase from the previous number of 15,079.000 Unit th for 2016. Albania Postal Services: Number of Simple Letters and Parcels data is updated yearly, averaging 5,712.300 Unit th from Dec 1993 (Median) to 2017, with 25 observations. The data reached an all-time high of 17,073.000 Unit th in 2011 and a record low of 844.000 Unit th in 1995. Albania Postal Services: Number of Simple Letters and Parcels data remains active status in CEIC and is reported by Institute of Statistics. The data is categorized under Global Database’s Albania – Table AL.TB001: Postal and Telecommunication Services.

Market Overview:

The global Structured Cabling system sales market is expected to grow at a CAGR of 7.5% from 2022 to 2030. The growth is mainly driven by the increasing demand for data communication and networking in various industries. In addition, the increasing adoption of cloud-based solutions is also contributing to the growth of the structured cabling system market.

Product Definition:

Structured cabling system sales is an important part of any business. It enables companies to keep their networks running smoothly and efficiently. A structured Cabling System is a type of cabling system that consists of a series of interconnected cables and connectors.

Cables:

Cables are used in structured cabling systems for the transmission of electrical signals and power. Cables are a type of electrical wiring that carry electric current from one point to another. They are made up of various materials such as copper, aluminum, plastic insulation, and fiber optic cables.

Copper:

Copper is a soft, malleable metal that is colorless in nature. Copper is a metal that has been used for centuries because of its many advantages. Copper is strong and durable, making it a good choice for cables and other components in a structured cabling system. It also conducts electricity well, which makes it ideal for wiring systems in buildings and other structures.

Data Center Structured Cabling Systems play a crucial role in the modern digital infrastructure. As data centers continue to expand and evolve, the need for efficient and reliable cabling systems becomes paramount. These systems are designed to support the high-speed data transfer and connectivity requirements of contemporary data centers, ensuring seamless communication and data flow. The structured cabling systems in data centers are engineered to accommodate future growth and technological advancements, providing a scalable solution that can adapt to the ever-changing demands of the digital world. By implementing structured cabling systems, data centers can achieve enhanced performance, reduced downtime, and improved operational efficiency, which are essential for maintaining competitiveness in the fast-paced technology landscape.

Fiber Optic:

Fiber optic cables are made of glass or plastic and use light to transmit data. They are faster, more reliable, and easier to install than copper cables. Fiber optic cables can also travel through walls and under floors.

Communication Outlets:

Communication outlets are the physical connectors that allow devices to communicate with each other. Communication outlets are often easy to use and install, making them an ideal choice for users who need quick and easy access to network connections.

Patch Panels & Cross Connects:

Patch Panels and cross-connects are the essential components of a structured cabling system. They allow cable operators to route cables in a flexible and organized fashion, making it easier to connect devices together. Patch panels come in different shapes and sizes, so they can be used for a variety of applications. Cross connects are similar to patch panels, but they allow multiple cables to be connected together at once.

Patch Cords & Cable Assemblies:

Patch cords and cable assemblies are a type of electrical wiring that connect two or more pieces of equipment. Some of the advantages of using patch cords and cable assemblies include their low cost, durability, and flexibility.

Racks & Cabinets:

Racks & Cabinets are a type of storage system that is used to organize and store electronic equipment. They come in different sizes and can be mounted on walls or ceilings. Racks & Cabinets have many advantages, including the ability to organize and store electronic equipment, the ability to mount electronic equipment on the wall or ceiling, and the ability to hide electronic equipment from view.

Application Insights:

The industry has been segmented on the basis of application into IT & telecommunication, residential & commercial, government & education, and transportation. The IT and telecommunication segment dominated the global Structured Cabling System sales market in 2014 with a share of over 40%. This is attributed to the increasing demand for high-speed data transfer services across networks. Furthermore,

This dataset supports the publication in Electrophoresis entitled 'Short Communication: A simple and accurate method of measuring the Zeta-Potential of microfluidic channels'. This is the original dataset used to create Figures 2B, 2C and Figure 3. It also contains the uncertainty estimations of the measured zeta potential displayed in Figure 3 computed from the original dataset for each of the conductivity solutions used in the work: 1.5 mS/m, 5.2 mS/m and 11.4 mS/m.

The dark analytics market, encompassing the use of advanced analytics techniques on unstructured and underutilized data, is experiencing robust growth. A 24.90% Compound Annual Growth Rate (CAGR) from 2019 to 2024 suggests a significant expansion, driven by increasing data volumes, the need for improved decision-making, and advancements in artificial intelligence (AI) and machine learning (ML). Key drivers include the rising adoption of cloud-based analytics platforms, the growing demand for predictive modeling across various sectors, and the need for enhanced cybersecurity and fraud detection. The BFSI (Banking, Financial Services, and Insurance) sector is a major adopter, leveraging dark analytics for risk management, fraud prevention, and personalized customer experiences. Healthcare is another significant segment, utilizing dark analytics for improved diagnostics, patient care optimization, and drug discovery. While data privacy concerns and the complexity of analyzing unstructured data present challenges, the overall market trajectory remains strongly positive, with considerable potential for future expansion. The market segmentation highlights the diverse applications of dark analytics. Predictive analytics, focusing on forecasting future outcomes, is a prominent segment, followed by prescriptive analytics which provides recommendations for optimal actions. Descriptive analytics, while foundational, continues to play a crucial role in understanding existing data patterns. Geographically, North America, particularly the United States, currently holds a dominant market share due to its advanced technological infrastructure and early adoption of analytics solutions. However, Asia-Pacific is anticipated to witness substantial growth in the coming years, propelled by rapid digitalization and increasing investment in data-driven technologies across sectors like e-commerce and telecommunications. Major players like IBM, SAP, Amazon Web Services, and Microsoft are actively involved in developing and offering dark analytics solutions, further fueling market expansion and innovation. Considering the 2019-2024 CAGR of 24.90%, a reasonable estimation for the market size in 2025 could range between $8-12 billion (assuming a starting point in 2019). The sustained growth rate would then propel the market towards a substantially larger size by 2033. Recent developments include: November 2022: The hybrid data company, Cloudera, has introduced a program called the Cloudera Partner Network that pays and honors partners for their role in the firm's go-to-market performance. Customers participating in this program will become familiar with contemporary data techniques built on the Cloudera hybrid data platform. The participants will use cutting-edge solutions, including the easy-to-use Marketing Automation Platform and Asset Library., Feb 2023: The software development firm N-iX has been granted Amazon Redshift and Amazon EMR Service Delivery Designation. For easy use of big data frameworks like Apache Hadoop on Amazon EMR, N-iX offers expertise in developing and deploying big data analytics applications. The N-iX team assisted its customer, a supplier of in-flight connectivity and entertainment, in one of its projects by helping with the migration of the client's data solution to a cloud-based platform. The N-iX team created the Amazon data platform for this project, which collected all the data from more than 20 distinct sources.. Key drivers for this market are: Increasing Adoption Rates of Machine Learning and Artificial Intelligence, Rapid Growth in Generated Data Volume and Variety Owing to Adoption of IoT. Potential restraints include: Increasing Adoption Rates of Machine Learning and Artificial Intelligence, Rapid Growth in Generated Data Volume and Variety Owing to Adoption of IoT. Notable trends are: Retail and E-commerce to Hold Significant Growth.

Rollable Ribbon Fiber Cable Market Outlook

According to our latest research, the Global Rollable Ribbon Fiber Cable market size was valued at $1.45 billion in 2024 and is projected to reach $4.12 billion by 2033, expanding at a robust CAGR of 12.5% during the forecast period of 2024–2033. This remarkable growth trajectory is primarily fueled by the surging demand for high-density, flexible, and easily deployable fiber optic solutions across telecommunications, data centers, and FTTx applications. As network infrastructure modernization accelerates worldwide to support the exponential rise in data consumption, rollable ribbon fiber cables are increasingly favored for their superior packing density, cost-effective installation, and enhanced scalability, making them a cornerstone in next-generation broadband and enterprise network deployments.

Regional Outlook

North America continues to command the largest share of the global rollable ribbon fiber cable market, accounting for over 34% of total revenue in 2024. The region's dominance is attributed to its mature telecommunications infrastructure, widespread adoption of 5G and FTTx networks, and a robust ecosystem of network operators and technology vendors. The United States, in particular, has witnessed significant investments in broadband expansion, data center construction, and smart city initiatives, all of which necessitate high-capacity, easily deployable fiber solutions. Regulatory incentives, such as federal funding for rural broadband and public-private partnerships, further propel market growth. North American enterprises are also early adopters of advanced cable technologies, leveraging rollable ribbon fiber cables to optimize network performance and reduce deployment timelines, thus reinforcing the region’s leadership position.

Asia Pacific stands out as the fastest-growing region in the rollable ribbon fiber cable market, projected to register an impressive CAGR of 15.2% between 2024 and 2033. This growth is driven by aggressive investments in digital infrastructure across China, India, Japan, and Southeast Asian nations, where rapid urbanization and surging internet penetration are creating unprecedented demand for high-speed connectivity. Governments in the region are prioritizing fiberization projects, 5G rollouts, and smart city development, spurring large-scale deployments of rollable ribbon fiber cables. Additionally, the proliferation of hyperscale data centers and cloud services is fueling demand for high-density, space-saving cabling solutions. Asia Pacific's manufacturing prowess and cost advantages also attract global players to set up production facilities, further catalyzing regional market expansion.

Emerging economies in Latin America, the Middle East, and Africa are gradually embracing rollable ribbon fiber cable technology, albeit at a slower pace due to infrastructural and economic constraints. These regions face unique adoption challenges, including limited capital expenditure, regulatory bottlenecks, and a shortage of skilled labor for advanced fiber deployments. However, localized demand is growing as governments and private sector players recognize the importance of digital transformation for economic development. Policy reforms aimed at liberalizing the telecom sector, coupled with international funding for broadband expansion, are beginning to bridge the digital divide. As these markets mature, tailored solutions and capacity-building initiatives will be critical to unlocking the full potential of rollable ribbon fiber cable technology.

Report Scope

The size of the Operations Management in the Telecom Industry market was valued at USD 77.65 Million in 2024 and is projected to reach USD 126.00 Million by 2033, with an expected CAGR of 7.16% during the forecast period. Recent developments include: April 2022 - The Ministry of Railways and the Centre for Development of Telematics (C-DOT) have signed an MoU to modernize telecommunication in Indian Railways for public safety and security services. The MoU was signed for coordination, resource sharing, and to deliver and implement C-DOT's telecom solutions and services in the railway's network., November 2021 - AWS announced the availability of a private 5G service for enterprises named AWS Private 5G. AWS is rolling out an easy-to-procure starter kit for a fully-managed, pay-as-you-go, private cellular service, which lays the groundwork for expanded offerings, direct-to-enterprise, and through AWS's communication service provider (CSP) partners.. Key drivers for this market are: Increasing Operational Costs and Complexity. Potential restraints include: , Stringent Government Regulations on Data Security. Notable trends are: Cloud is Expected to Witness Significant Growth.

The original research publication that uses the dataset evaluated the application of the 5Q approach (5Q) combined with interactive voice response (IVR) call campaigns for agile data collection. The dataset includes 37’503 call metadata from 102 IVR call campaigns and among five countries. The dataset provides insights to call status, average call duration, reached IVR blocks, and differences in response rate between different call types and survey topics.

# FiN-2 Large-Scale Real-World PLC-Dataset

## About
#### FiN-2 dataset in a nutshell:
FiN-2 is the first large-scale real-world dataset on data collected in a powerline communication infrastructure. Since the electricity grid is inherently a graph, our dataset could be interpreted as a graph dataset. Therefore, we use the word node to describe points (cable distribution cabinets) of measurement within the low-voltage electricity grid and the word edge to describe connections (cables) in between them. However, since these are PLC connections, an edge does not necessarily have to correspond to a real cable; more on this in our paper.
FiN-2 shows measurements that relate to the nodes (voltage, total harmonic distortion) as well as to the edges (signal-to-noise ratio spectrum, tonemap). In total, FiN-2 is distributed across three different sites with a total of 1,930,762,116 node measurements each for the individual features and 638,394,025 edge measurements each for all 917 PLC channels. All data was collected over a 25-month period from mid-2020 to the end of 2022.
We propose this dataset to foster research in the domain of grid automation and smart grid. Therefore, we provide different example use cases in asset management, grid state visualization, forecasting, predictive maintenance, and novelty detection. For more decent information on this dataset, please see our [paper](https://arxiv.org/abs/2209.12693).

* * *
## Content
FiN-2 dataset splits up into two compressed `csv-Files`: *nodes.csv* and *edges.csv*.

All files are provided as a compressed ZIP file and are divided into four parts. The first part can be found in this repo, while the remaining parts can be found in the following:
- https://zenodo.org/record/8328105
- https://zenodo.org/record/8328108
- https://zenodo.org/record/8328111

### Node data

| id | ts | v1 | v2 | v3 | thd1 | thd2 | thd3 | phase_angle1 | phase_angle2 | phase_angle3 | temp |
|----|----|----|----|----|----|----|----|----|----|----|----|----|----|
|112|1605530460|236.5|236.4|236.0|2.9|2.5|2.4|120.0|119.8|120.0|35.3|
|112|1605530520|236.9|236.6|236.6|3.1|2.7|2.5|120.1|119.8|120.0|35.3|
|112|1605530580|236.2|236.4|236.0|3.1|2.7|2.5|120.0|120.0|119.9|35.5|

- id / ts: Unique identifier of the node that is measured and timestemp of the measurement
- v1/v2/v3: Voltage measurements of all three phases
- thd1/thd2/thd3: Total harmonic distortion of all three phases
- phase_angle1/2/3: Phase angle of all three phases
- temp: Temperature in-circuit of the sensor inside a cable distribution unit (in °C)

### Edge data
| src | dst | ts | snr0 | snr1 | snr2 | ... | snr916 |
|----|----|----|----|----|----|----|----|
|62|94|1605528900|70|72|45|...|-53|
|62|32|1605529800|16|24|13|...|-51|
|17|94|1605530700|37|25|24|...|-55|

- src & dst & ts: Unique identifier of the source and target nodes where the spectrum is measured and time of measurement
- snr0/snr1/.../snr916: 917 SNR measurements in tenths of a decibel (e.g. 50 --> 5dB).

### Metadata
Metadata that is provided along with the data covers:

- Number of cable joints
- Cable properties (length, type, number of sections)
- Relative position of the nodes (location, zero-centered gps)
- Adjacent PV or wallbox installations
- Year of installation w.r.t. the nodes and cables

Since the electricity grid is part of the critical infrastructure, it is not possible to provide exact GPS locations.

* * *
## Usage
Simple data access using pandas:

```
import pandas as pd

nodes_file = "nodes.csv.gz" # /path/to/nodes.csv.gz
edges_file = "edges.csv.gz" # /path/to/edges.csv.gz

# read the first 10 rows
data = pd.read_csv(nodes_file, nrows=10, compression='gzip')

# read the row number 5 to 15
data = pd.read_csv(nodes_file, nrows=10, skiprows=[i for i in range(1,6)], compression='gzip')

# ... same for the edges
```

Compressed csv-data format was used to make sharing as easy as possible, however it comes with significant drawbacks for machine learning. Due to the inherent graph structure, a single snapshot of the whole graph consists of a set of node and edge measurements. But due to timeouts, noise and other disturbances, nodes sometimes fail in collecting the data, wherefore the number of measurements for a specific timestamp differs. This, plus the high sparsity of the graph, leads to a high inefficiency when using the csv-format for an ML training.
To utilize the data in an ML pipeline, we recommend other data formats like [datadings](https://datadings.readthedocs.io/en/latest/) or specialized database solutions like [VictoriaMetrics](https://victoriametrics.com/).

### Example use case (voltage forecasting)

Forecasting of the voltage is one potential use cases. The Jupyter notebook provided in the repository gives an overview of how the dataset can be loaded, preprocessed and used for ML training. Thereby, a MinMax scaling was used as simple preprocessing and a PyTorch dataset class was created to handle the data. Furthermore, a vanilla autoencoder is utilized to process and forecast the voltage into the future.

Snapshot img

Web Real Time Communication (WebRTC) Market Size 2025-2029

The web real time communication (WebRTC) market size is forecast to increase by USD 247.7 billion, at a CAGR of 62.6% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing demand for easy-to-use real-time communication solutions. This trend is further fueled by the integration of WebRTC with internet of things (IoT) sensors, enabling seamless communication between devices and users. However, the market faces challenges, primarily the lack of high-end video conferencing features, which may hinder its adoption in corporate environments. Companies seeking to capitalize on this market's opportunities should focus on enhancing the user experience and addressing the need for advanced video conferencing features.
By doing so, they can effectively navigate the competitive landscape and establish a strong presence in the rapidly evolving WebRTC market.

What will be the Size of the Web Real Time Communication (WebRTC) Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The Web Real-Time Communication (WebRTC) market continues to evolve, with dynamic applications across various sectors. Real-time video streaming, online gaming, and distance learning are key areas where WebRTC shines. Packet loss concealment, video conferencing, and WebRTC gateways ensure seamless communication. Adaptive bitrate streaming and interoperability testing maintain quality and compatibility. Signaling protocols and media negotiation facilitate session establishment. Jitter buffer and error correction optimize performance. Noise suppression and echo cancellation enhance audio processing. WebRTC SDKs and APIs simplify integration. Browser compatibility and live streaming expand reach.

Interactive broadcasting and peer-to-peer communication foster engagement. Network congestion control and session management ensure reliability. Media codecs and chat applications enrich user experience. WebRTC's continuous evolution includes advancements in signaling servers, performance benchmarking, and firewall traversal. The market's unfolding patterns reflect the ongoing integration of these features into innovative applications.

How is this Web Real Time Communication (WebRTC) Industry segmented?

The web real time communication (WebRTC) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Video
  Voice
  Data sharing


Platform

  Mobile
  Browser
  UC


End-User

  Retail
  BFSI
  IT & Telecom
  Media & Entertainment
  Third-Party Logistics (3PL)
  Retail
  BFSI
  IT & Telecom
  Media & Entertainment
  Third-Party Logistics (3PL)


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Application Insights

The video segment is estimated to witness significant growth during the forecast period.

Web Real Time Communication (WebRTC) technology is revolutionizing business communication by enabling real-time, high-quality video streaming and conferencing directly through web and mobile applications. This innovative solution eliminates the need for additional software or plugins, providing a seamless user experience. The technology's reliability is ensured through features like jitter buffer, packet loss concealment, and error correction. WebRTC's versatility extends beyond video conferencing. It's used extensively in online gaming, distance learning, and interactive broadcasting, offering a more immersive and harmonious communication experience. The technology's media negotiation capabilities allow for adaptive bitrate streaming, ensuring optimal performance even in network congestion.

WebRTC's interoperability is crucial, as it allows for peer-to-peer communication and firewall traversal, making it a preferred choice for remote collaboration and real-time chat applications. Signaling protocols facilitate session establishment and management, while media codecs support various audio and video formats. WebRTC's SDKs and APIs, such as getUserMedia, RTCPeerConnection, and RTCDataChannel, are built into modern browsers, making implementation easy and efficient. WebRTC gateways further enhance its functionality by enabling interoperability between WebRTC and non-WebRTC endpoints. Performance benchmarking and network congestion control are essential for maintaining a high-quality user experience. WebRTC solutions address these challenges through advanced techniques like echo cancellation and noise suppre

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