The website localization market, valued at $521 million in 2025, is projected to experience robust growth, driven by the increasing global reach of businesses and the rising demand for multilingual online experiences. A Compound Annual Growth Rate (CAGR) of 5.8% from 2025 to 2033 indicates a significant expansion of this market, exceeding $800 million by 2033. Key drivers include the escalating need to cater to diverse international audiences, improve customer engagement and conversion rates, and enhance brand reputation in global markets. The growing adoption of e-commerce and the expansion of digital marketing initiatives across borders further fuel this expansion. While the market segments – Large Enterprises and SMEs, along with Online and Offline service types – demonstrate varied growth trajectories, the shift towards online localization services is anticipated to be particularly pronounced, reflecting technological advancements and cost-effectiveness. Regional variations exist, with North America and Europe currently holding significant market shares; however, the Asia-Pacific region is expected to witness accelerated growth fueled by burgeoning internet penetration and economic expansion in developing economies. The competitive landscape is characterized by a mix of established players and emerging companies. Large multinational localization service providers such as RWS, Lionbridge (implied by the presence of RWS Moravia), and SDL (implied by the presence of several companies specializing in translation and localization) are competing with smaller, niche players specializing in specific languages or industries. The market is also seeing increasing consolidation through mergers and acquisitions, reflecting the strategic importance of localization capabilities for global business expansion. Potential restraints include the complexities of managing multilingual projects, ensuring linguistic accuracy, and adapting websites for culturally specific audiences. However, the ongoing development of advanced translation technologies such as AI-powered machine translation (often improved by human post-editing) is gradually mitigating these challenges and driving down costs, further bolstering market growth.

The global Marketing Localization Services market, valued at $8,093 million in 2025, is projected to experience robust growth, driven by the increasing globalization of businesses and the rising demand for culturally relevant marketing materials. A Compound Annual Growth Rate (CAGR) of 6.3% from 2025 to 2033 indicates a significant market expansion, reaching an estimated value exceeding $13,000 million by 2033. This growth is fueled by several key factors. Firstly, the expanding digital landscape necessitates localized content across various platforms, including websites, social media, and mobile applications. Secondly, the increasing cross-border e-commerce activities necessitate precise translation and adaptation of marketing materials to resonate with diverse consumer groups. Finally, the rise of multilingual customer support enhances brand loyalty and customer satisfaction, further bolstering the demand for marketing localization services. The market is segmented by application (large enterprises and SMEs) and type (cloud-based and web-based solutions), reflecting the diverse needs of businesses of varying sizes and technological preferences. While the cloud-based segment currently holds a larger market share, the web-based segment is expected to witness significant growth due to its cost-effectiveness and ease of access. Geographic distribution reveals strong growth potential across emerging markets in Asia Pacific and Latin America, in addition to sustained demand in North America and Europe. The competitive landscape is marked by a blend of established players and emerging companies, each offering specialized solutions. Key players are investing in advanced technologies like artificial intelligence (AI) and machine learning (ML) to enhance translation accuracy and efficiency, further driving market evolution. However, challenges exist, including ensuring consistent brand messaging across diverse markets, maintaining data security and privacy during the localization process, and managing the complexities of linguistic nuances. Successfully navigating these challenges through strategic partnerships, technological innovation, and a focus on customer-centric solutions will be crucial for players seeking sustained market success in the burgeoning field of marketing localization.

The NAVER LABS localization datasets are 5 new indoor datasets for visual localization in challenging real-world environments. They were captured in a large shopping mall and a large metro station in Seoul, South Korea, using a dedicated mapping platform consisting of 10 cameras and 2 laser scanners. In order to obtain accurate ground truth camera poses, we used a robust LiDAR SLAM which provides initial poses that are then refined using a novel structure-from-motion based optimization. The datasets are provided in the kapture format and contain about 130k images as well as 6DoF camera poses for training and validation. We also provide sparse Lidar-based depth maps for the training images. The poses of the test set are withheld to not bias the benchmark.

INTRODUCTION

The goal of these LPWAN datasets is to provide the global research community with a benchmark tool to evaluate fingerprint localization algorithms in large outdoor environments with various properties. An identical collection methodology was used for all datasets: during a period of three months, numerous devices containing a GPS receiver periodically obtained new location data, which was sent to a local data server via a Sigfox or LoRaWAN message. Together with network information such as the receiving time of the message, base station IDs' of all receiving base stations and the Received Signal Strength Indicator (RSSI) per base station, this location data was stored in one of the three LPWAN datasets:

lorawan_dataset_antwerp.csv

130 430 LoRaWAN messages, obtained in the city center of Antwerp

sigfox_dataset_antwerp.csv

14 378 Sigfox messages, obtained in the city center of Antwerp

sigfox_dataset_rural.csv

25 638 Sigfox messages, obtained in a rural area between Antwerp and Ghent

As the rural and urban Sigfox datasets were recorded in adjacent areas, many base stations that are located at the border of these areas can be found in both datasets. However, they do not necessarily share the same identifier: e.g. ‘BS 1’ in the urban Sigfox dataset could be the same base station as ‘BS 36’ in the rural Sigfox dataset. If the user intends to combine both Sigfox datasets, the mapping of the ID's of these base stations can be found in the file:

sigfox_bs_mapping.csv

The collection methodology of the datasets, and the first results of a basic fingerprinting implementation are documented in the following journal paper: http://www.mdpi.com/2306-5729/3/2/13

UPDATES IN VERSION 1.2

In this version of the LPWAN dataset, only the LoRaWAN set has been updated. The Sigfox datasets remain identical to version 1.0 and 1.1. The main updates in the LoRaWAN set are the following:

New data: the LoRaWAN messages in the new set are collected 1 year after the previous dataset version. To be consistent with the previous versions, the new LoRaWAN set is uploaded in the same .CSV format as before. This upload can still be found in this repository as ‘lorawan_dataset_antwerp.csv’.

More gateways: Compared to the previous dataset, 4 gateways were added to the LoRaWAN network. The RSSI of these gateways are shown in columns ‘BS 69’, ‘BS 70’,‘BS 71’ and ‘BS 72’. All other ‘BS’ columns are in the same order as in previous dataset versions.

More metadata: In the previous LoRaWAN dataset, metadata was limited to 3 receiving gateways per message. In the new dataset version, metadata from all receiving gateways is included in every message. Moreover, some gateways provide a timestamp with nanosecond precision, which can be used to evaluate Time Difference of Arrival localization methods with LoRaWAN.

2 file formats: As more metadata becomes available, we find it important to share the dataset in a clearer overview. This also allows researchers to evaluate the performance of LoRaWAN in an urban environment. Therefore, we publish the new LoRaWAN dataset as a .CSV file as described above, but also as a .JSON file (lorawan_antwerp_2019_dataset.json.txt, the .txt file type had to be appended, otherwise the file could not be uploaded to Zenodo) An example of one message in this JSON format can be seen below:

JSON format description:

HDOP: Horizontal Dilution of Precision

dev_addr: LoRaWAN device address

dev_eui: LoRaWAN device EUI

sf: Spreading factor

channel: TX channel (EU region)

payload: application payload

adr: Adaptive Data Rate (1 = enabled, 0= disabled)

counter: device uplink message counter

latitude: Groundtruth TX location latitude

longitude: Groundtruth TX location longitude

airtime: signal airtime (seconds)

gateways:

rssi: Received Signal Strength

esp: Estimated Signal Power

snr: Signal-to-Noise Ratio

ts_type: Timestamp type. If this says "GPS_RADIO", a nanosecond precise timestamp is available

time: time of arrival at the gateway

id: gateway ID

JSON example

{ "hdop": 0.7, "dev_addr": "07000EFE", "payload": "008d000392d54c4284d18c403333333f04682aa9410500e8fd4106cabdbc420f00db0d470ce32ac93f0d582be93f0bfa3f8d3f", "adr": 1, "latitude": 51.20856475830078, "counter": 31952, "longitude": 4.400575637817383, "airtime": 0.112896, "gateways": [ { "rssi": -115, "esp": -115.832695, "snr": 6.75, "rx_time": { "ts_type": "None", "time": "2019-01-04T08:59:53.079+01:00" }, "id": "08060716" }, { "rssi": -116, "esp": -125.51497, "snr": -9.0, "rx_time": { "ts_type": "GPS_RADIO", "time": "2019-01-04T08:59:53.962029179+01:00" }, "id": "FF0178DF" } ], "dev_eui": "3432333853376B18", "sf": 7, "channel": 8 }

The global translation and localization services market size was valued at USD 46.5 billion in 2021 and is projected to grow at a compound annual growth rate (CAGR) of 6.4% from 2022 to 2030. The growth of the market is attributed to the increasing globalization of businesses, the rise of e-commerce, and the need for accurate and culturally sensitive translations. The key drivers of the translation and localization services market include the rising demand for multilingual content, the increasing number of cross-border collaborations, and the growing popularity of e-commerce. The market is also being driven by the emergence of new technologies, such as machine translation and artificial intelligence, which are making it easier and more affordable to translate content. The large enterprises segment is expected to hold the largest share of the market due to the high demand for localization services in multinational companies. However, the SMEs segment is expected to grow at a faster CAGR during the forecast period due to the increasing need for affordable and efficient translation services by small and medium-sized businesses. North America is the dominant region in the translation and localization services market due to the presence of a large number of multinational companies and the high demand for multilingual content.

The global software and mobile app localization market is experiencing robust growth, driven by the increasing demand for software and applications across diverse linguistic and cultural regions. The market's expansion is fueled by the rising adoption of smartphones and mobile applications worldwide, coupled with the globalization of businesses seeking to reach wider customer bases. Key market drivers include the increasing need for multilingual user interfaces, growing international trade, and the imperative for businesses to cater to culturally diverse audiences. Furthermore, the trend toward personalized user experiences necessitates localization efforts that extend beyond simple translation to encompass cultural adaptation and contextualization. While the market faces challenges such as the high cost of localization and the scarcity of skilled linguists in certain languages, these obstacles are being mitigated by advancements in machine translation technology and the emergence of specialized localization service providers. The competitive landscape is characterized by a mix of large multinational companies and smaller, specialized firms offering a diverse range of services, from machine translation to expert human translation, catering to both SMEs and large enterprises. The North American market currently holds a significant share, reflecting the region's strong technological advancement and adoption of mobile applications, but the Asia-Pacific region is poised for substantial growth, driven by rapid economic expansion and increasing internet penetration in countries like India and China. Segment-wise, the demand for machine translation solutions is escalating due to their cost-effectiveness and speed, although human expert translation remains critical for ensuring high accuracy and cultural appropriateness in complex contexts. The large enterprise segment contributes significantly to the overall market value, reflecting their larger budgets and substantial international operations. However, the SME segment is witnessing a notable increase in localization adoption, as they seek to tap into new global markets. This suggests a growing opportunity for solutions that are both effective and financially accessible to smaller businesses. Looking ahead, the future of the software and mobile app localization market is bright, with ongoing technological advancements and the increasing globalization of businesses driving continued expansion over the coming years. The market's trajectory suggests substantial growth opportunities for both established players and emerging businesses that can effectively address the growing demand for high-quality, culturally relevant localized applications.

The global Website and Software Localization Services market is experiencing robust growth, driven by the increasing demand for multilingual content across diverse industries. The market's expansion is fueled by the rising globalization of businesses, the proliferation of digital platforms, and the need to reach wider customer bases internationally. The shift towards digitalization necessitates the localization of websites and software to improve user experience and increase market penetration in various regions. While large enterprises are significant contributors, the increasing adoption of localization services by SMEs indicates a broad-based market expansion. The strong preference for machine translation solutions for cost-effective solutions is balanced by continued reliance on expert human translation for critical applications demanding high accuracy and nuanced understanding. This creates a diverse market landscape with opportunities for both technology-driven and human-centric service providers. North America and Europe currently dominate the market, but Asia-Pacific is expected to witness significant growth in the coming years, driven by increasing internet penetration and a burgeoning digital economy in countries like India and China. Challenges include managing the complexity of multiple languages and cultural contexts, ensuring translation consistency, and adapting to rapid technological advancements in AI-powered translation tools. The forecast period (2025-2033) anticipates continued expansion, with a projected CAGR exceeding the industry average, reflecting a consistently high demand. Key players in the market are investing heavily in research and development, refining their offerings with AI-powered solutions and enhanced quality control mechanisms. Competition is intense, with both large multinational corporations and specialized niche players vying for market share. Strategic partnerships and mergers and acquisitions are becoming increasingly common as companies seek to enhance their service portfolios and broaden their global reach. The market segmentation by application (SMEs vs. Large Enterprises) and type (Machine Translation vs. Expert Translation) reflects varying needs and budgetary constraints, further shaping the market dynamics and offering unique opportunities for different providers.

The global translation and localization services market is experiencing robust growth, driven by increasing globalization, the rise of e-commerce, and the expanding digital landscape. The market, currently valued in the billions (a precise figure requires the missing market size data; let's assume, based on industry reports, a 2025 market size of $50 billion for illustrative purposes), is projected to maintain a healthy Compound Annual Growth Rate (CAGR) for the forecast period of 2025-2033. This growth is fueled by several key factors. Firstly, businesses are increasingly recognizing the importance of reaching international markets, necessitating the translation and localization of their products, websites, and marketing materials. Secondly, technological advancements in translation tools and artificial intelligence (AI) are improving efficiency and reducing costs, making these services more accessible to a wider range of businesses, from large enterprises to SMEs. Finally, the growing demand for multilingual content across various media, including documents, websites, software, and multimedia, further contributes to the market's expansion. However, market growth is not without its challenges. Competition is fierce, with numerous players ranging from large multinational corporations to smaller specialized firms. Maintaining quality while managing costs is a constant balancing act for service providers. Further, fluctuations in global economic conditions can impact demand, particularly in sectors heavily reliant on international trade. Despite these restraints, the long-term outlook remains positive, particularly for those companies specializing in niche areas or offering innovative technological solutions. The market segmentation shows strong demand across all application areas (large enterprises and SMEs) and types of localization services (document, website, software, multimedia), indicating a diverse and resilient market poised for continued growth driven by factors such as increased digital interactions and a globalized economy. Market penetration within emerging economies also presents significant growth opportunities.

According to Cognitive Market Research, the global Localization Software Market size will be USD 6251.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 10.8% from 2024 to 2031.

North America held the major market of more than 40 % of the global revenue with a market size of USD 2500.48 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.0 % from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 1875.36 million.
Asia Pacific held the market of around 5 % of the global revenue with a market size of USD 1437.78 million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.8 % from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 312.56 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.2 % from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 125.02 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.5 % from 2024 to 2031.
The large enterprises had the largest share in the global Localization Software Market by application.

Market Dynamics of Localization Software Market

Key Drivers of Localization Software Market

Rising Need for Multilingual Software to Boost Market Growth

In response to the imperative for global businesses to connect with customers in diverse languages, the demand for multilingual software is on the rise. Companies are strategically investing in software localization tools to guarantee the accessibility of their products and services to a broader audience. This entails offering localized versions of their offerings in multiple languages, accompanied by tailored user interfaces and content. Moreover, multilingual software catalyzes expanding market reach, allowing companies to target customers in previously untapped territories. By embracing multilingual solutions, businesses can effectively bridge linguistic barriers, enhancing their global presence and fostering deeper engagement with international audiences.

Cost-Effective Language Support Solutions to Boost Market Growth

As the demand for multilingual software continues to surge, there's an escalating need for cost-effective language support solutions. Companies are actively seeking economical options to trim down localization expenses without compromising on language support quality. Software localization tools emerge as a viable solution, enabling companies to streamline costs through automated translation and localization services. These tools facilitate the swift and efficient creation of localized product versions, further optimizing expenditure. Moreover, the market witnesses a growing demand for user-friendly localization tools catering to the diverse needs of businesses. Additionally, there's a notable uptick in the adoption of cloud-based localization solutions, offering flexibility and scalability to meet evolving demands. Concurrently, the rising interest in translation automation software underscores the industry's pursuit of efficient, resource-saving solutions to address the burgeoning demand for multilingual software.

Restraint Factors Of Localization Software Market

Skilled Resource Shortage in Software Localization Tool Implementation to Limit Market Growth

A significant hindrance for the Global Software Localization Tools Market is the need for more skilled resources for tool implementation. Companies need help in securing personnel with the requisite knowledge and expertise to deploy software localization tools efficiently. This need for more language-specific proficiency poses challenges for companies to adapt to evolving customer preferences and maintain competitiveness. Consequently, organizations need to work on staying abreast of market dynamics due to the shortage of skilled personnel. Moreover, this scarcity restricts access to the latest technology and tools available in the market, further impeding the effective implementation of software localization solutions. In addressing this challenge, companies must prioritize efforts to cultivate and attract skilled resources proficient in software localization, enabling them to effectively leverage these tools to meet evolving market demands and maintain a competitive edge.

Impact of Covid-19 on the Localizatio...

Game Localization Services Market Outlook

The global Game Localization Services market size was valued at approximately USD 2 billion in 2023 and is projected to reach USD 4.1 billion by 2032, growing at a robust CAGR of 8.5% during the forecast period. This growth is driven by the increasing demand for video games across various regions, coupled with the need to cater to diverse linguistic and cultural preferences. As the gaming industry expands globally, developers are increasingly recognizing the importance of localization services to ensure that games resonate well with local audiences, thereby amplifying their reach and profitability.

One of the primary growth factors contributing to the expansion of the game localization services market is the globalization of the gaming industry. As gaming companies aim to penetrate new markets, the demand for comprehensive localization services to cater to specific cultural and linguistic nuances has surged. The proliferation of high-speed internet and the rise of digital distribution channels have made games more accessible worldwide, thus necessitating tailored localization to enhance user experience and increase market penetration. Game developers and publishers are investing heavily in localization to capture the attention of gamers across different regions, fostering market growth.

Additionally, advancements in technology are playing a crucial role in the growth of the game localization services market. The advent of artificial intelligence and machine learning in localization processes has significantly improved the efficiency and accuracy of translations and cultural adaptations. These technologies enable more seamless integration of language changes and cultural elements, thereby reducing time and costs associated with localization. The continuous innovation in localization tools and software is also encouraging smaller game developers to utilize these services, further driving market expansion.

The increasing diversity in game genres and platforms is another significant factor propelling the market. With a wide range of game genres, each requiring specific localization strategies, the demand for specialized services has increased. Moreover, the rise in cross-platform gaming, including consoles, PCs, and mobile devices, has heightened the need for localized content that is consistent across different platforms. This diversification necessitates comprehensive localization strategies that can cater to various gaming preferences and platforms, thereby contributing to the market’s growth.

Regionally, the Asia Pacific region is expected to witness substantial growth in the game localization services market. This is largely attributed to the booming gaming industries in countries like China, Japan, and South Korea. These countries have a high demand for localized content due to their unique cultural and language needs. North America and Europe are also significant markets, with a strong presence of major gaming companies and a large base of bilingual consumers. The Middle East & Africa and Latin America are emerging markets, showing promising growth potential due to increasing internet penetration and rising gaming populations.

Service Type Analysis

The game localization services market by service type is categorized into translation, cultural adaptation, voiceover, quality assurance, and others. Among these, translation services form the backbone of game localization, as they are crucial for converting in-game text and dialogue into various languages. The demand for high-quality translation services is increasing as gamers expect seamless and error-free language adaptations that do not distort the original game narrative. Companies are leveraging advanced translation software and professional linguists to provide accurate and contextually appropriate translations, ensuring a genuine gaming experience for players across different regions.

Cultural adaptation is another critical aspect of game localization services, as it involves tailoring game content to align with the cultural norms and sensibilities of the target market. This includes modifying visual elements, in-game symbols, and references that may not be culturally appropriate or relevant in certain regions. Cultural adaptation ensures that games are socially acceptable and engaging for local audiences, thereby enhancing player immersion and satisfaction. As gaming companies expand into new markets, the demand for cultural adaptation services is expected to grow, highlighting its significant role in the localization process.

Update: New version includes additional samples taken in November 2022.

Dataset Description

This dataset is a large-scale set of measurements for RSS-based localization. The data consists of received signal strength (RSS) measurements taken using the POWDER Testbed at the University of Utah. Samples include either 0, 1, or 2 active transmitters.

The dataset consists of 5,214 unique samples, with transmitters in 5,514 unique locations. The majority of the samples contain only 1 transmitter, but there are small sets of samples with 0 or 2 active transmitters, as shown below. Each sample has RSS values from between 10 and 25 receivers. The majority of the receivers are stationary endpoints fixed on the side of buildings, on rooftop towers, or on free-standing poles. A small set of receivers are located on shuttles which travel specific routes throughout campus.

Dataset Description Sample Count Receiver Count

No-Tx Samples 46 10 to 25

1-Tx Samples 4822 10 to 25

2-Tx Samples 346 11 to 12

The transmitters for this dataset are handheld walkie-talkies (Baofeng BF-F8HP) transmitting in the FRS/GMRS band at 462.7 MHz. These devices have a rated transmission power of 1 W. The raw IQ samples were processed through a 6 kHz bandpass filter to remove neighboring transmissions, and the RSS value was calculated as follows:

(RSS = \frac{10}{N} \log_{10}\left(\sum_i^N x_i^2 \right) )

Measurement Parameters Description

Frequency 462.7 MHz

Radio Gain 35 dB

Receiver Sample Rate 2 MHz

Sample Length N=10,000

Band-pass Filter 6 kHz

Transmitters 0 to 2

Transmission Power 1 W

Receivers consist of Ettus USRP X310 and B210 radios, and a mix of wide- and narrow-band antennas, as shown in the table below Each receiver took measurements with a receiver gain of 35 dB. However, devices have different maxmimum gain settings, and no calibration data was available, so all RSS values in the dataset are uncalibrated, and are only relative to the device.

Usage Instructions

Data is provided in .json format, both as one file and as split files.

import json data_file = 'powder_462.7_rss_data.json' with open(data_file) as f: data = json.load(f)

The json data is a dictionary with the sample timestamp as a key. Within each sample are the following keys:

rx_data: A list of data from each receiver. Each entry contains RSS value, latitude, longitude, and device name.

tx_coords: A list of coordinates for each transmitter. Each entry contains latitude and longitude.

metadata: A list of dictionaries containing metadata for each transmitter, in the same order as the rows in tx_coords

File Separations and Train/Test Splits

In the separated_data.zip folder there are several train/test separations of the data.

all_data contains all the data in the main JSON file, separated by the number of transmitters.

stationary consists of 3 cases where a stationary receiver remained in one location for several minutes. This may be useful for evaluating localization using mobile shuttles, or measuring the variation in the channel characteristics for stationary receivers.

train_test_splits contains unique data splits used for training and evaluating ML models. These splits only used data from the single-tx case. In other words, the union of each splits, along with unused.json, is equivalent to the file all_data/single_tx.json.

The random split is a random 80/20 split of the data.

special_test_cases contains the stationary transmitter data, indoor transmitter data (with high noise in GPS location), and transmitters off campus.

The grid split divides the campus region in to a 10 by 10 grid. Each grid square is assigned to the training or test set, with 80 squares in the training set and the remainder in the test set. If a square is assigned to the test set, none of its four neighbors are included in the test set. Transmitters occuring in each grid square are assigned to train or test. One such random assignment of grid squares makes up the grid split.

The seasonal split contains data separated by the month of collection, in April, July, or November

The transportation split contains data separated by the method of movement for the transmitter: walking, cycling, or driving. The non-driving.json file contains the union of the walking and cycling data.

campus.json contains the on-campus data, so is equivalent to the union of each split, not including unused.json.

Digital Surface Model

The dataset includes a digital surface model (DSM) from a State of Utah 2013-2014 LiDAR survey. This map includes the University of Utah campus and surrounding area. The DSM includes buildings and trees, unlike some digital elevation models.

To read the data in python:

import rasterio as rio import numpy as np import utm

dsm_object = rio.open('dsm.tif') dsm_map = dsm_object.read(1) # a np.array containing elevation values dsm_resolution = dsm_object.res # a tuple containing x,y resolution (0.5 meters) dsm_transform = dsm_object.transform # an Affine transform for conversion to UTM-12 coordinates utm_transform = np.array(dsm_transform).reshape((3,3))[:2] utm_top_left = utm_transform @ np.array([0,0,1]) utm_bottom_right = utm_transform @ np.array([dsm_object.shape[0], dsm_object.shape[1], 1]) latlon_top_left = utm.to_latlon(utm_top_left[0], utm_top_left[1], 12, 'T') latlon_bottom_right = utm.to_latlon(utm_bottom_right[0], utm_bottom_right[1], 12, 'T')

Dataset Acknowledgement: This DSM file is acquired by the State of Utah and its partners, and is in the public domain and can be freely distributed with proper credit to the State of Utah and its partners. The State of Utah and its partners makes no warranty, expressed or implied, regarding its suitability for a particular use and shall not be liable under any circumstances for any direct, indirect, special, incidental, or consequential damages with respect to users of this product.

DSM DOI: https://doi.org/10.5069/G9TH8JNQ

Robots need to know their location to map of their surroundings but without global positioning data they need a map to identify their surroundings and estimate their location. Simultaneous localization and mapping (SLAM) solves these dual problems at once. SLAM does not depend on any kind of infrastructure and is thus a promising localization technology for NASA planetary missions and for many terrestrial applications as well. However, state-of-the-art SLAM depends on easily-recognizable landmarks in the robot's environment, which are lacking in barren planetary surfaces. Our work will develop a technology we call MeshSLAM, which constructs robust landmarks from associations of weak features extracted from terrain. Our test results will also show that MeshSLAM applies to all environments in which NASA's rovers could someday operate: dunes, rocky plains, overhangs, cliff faces, and underground structures such as lava tubes. Another limitation of SLAM for planetary missions is its significant data-association problems. As a robot travels it must infer its motion from the sensor data it collects, which invariably suffers from drift due to random error. To correct drift, SLAM recognize when the robot has returned to a previously-visited place, which requires searching over a great deal of previously-sensed data. Computation on such a large amount of memory may be infeasible on space-relevant hardware. MeshSLAM eases these requirements. It employs topology-based map segmentation, which limits the scope of a search. Furthermore, a faster, multi-resolution search is performed over the topological graph of observations. Mesh Robotics LLC and Carnegie Mellon University have formed a partnership to commercially develop MeshSLAM. MeshSLAM technology will be available via open source, to ease its adoption by NASA. In Phase 1 of our project we will show the feasibility of MeshSLAM for NASA and commercial applications through a series of focused technical demonstrations.

The global app localization service market size was valued at USD 4,785.6 million in 2025 and is projected to reach USD 13,401.5 million by 2033, growing at a CAGR of 12.3% during the forecast period. The increasing demand for localized apps in various industries, such as e-commerce, gaming, and healthcare, is driving the growth of the market. Additionally, the growing number of multinational companies with global operations is also contributing to the growth of the market. The market is segmented into type (online service, offline service), application (large enterprises, SMEs), and region (North America, South America, Europe, Middle East & Africa, Asia Pacific). North America is the largest market for app localization services due to the presence of a large number of multinational companies headquartered in the region. Europe is the second-largest market, followed by Asia Pacific. The Asia Pacific market is expected to grow at the highest CAGR during the forecast period due to the increasing demand for localized apps in emerging economies such as China and India.

According to Cognitive Market Research, the global Software Localization Tools market size is USD 6125.2 million in 2023 and will expand at a compound annual growth rate (CAGR) of 11.20% from 2023 to 2030.

North America held the major market of more than 40% of the global revenue with a market size of USD 2450.08 million in 2023. It will grow at a compound annual growth rate (CAGR) of 9.4% from 2023 to 2030.
Europe Software Localization Tools projected to expand at a compound annual growth rate (CAGR) of 11.20% from 2023 to 2030, Europe accounted for a share of over 30% of the global market size of USD 1837.56 million
Asia Pacific held the market of more than 23% of the global revenue with market size of USD 1408.80 million in 2023 and will grow at a compound annual growth rate (CAGR) of 13.2% from 2023 to 2030
Latin America market of more than 5% of the global revenue with a market size of USD 306.25 million in 2023 and will grow at a compound annual growth rate (CAGR) of 10.6% from 2023 to 2030
Middle East and Africa held the major market of more than 2% of the global revenue with market size of USD 122.50 million in 2023 and will grow at a compound annual growth rate (CAGR) of 10.9% from 2023 to 2030
The demand for Software Localization Tools is rising due to Increase in Demand for localized software to Provide Viable Market Output.
Demand for services remains higher in the Software Localization Tools market.
The Computer Assisted Translation (CAT) category held the highest Software Localization Tools market revenue share in 2023.

Increase in Demand for Localized Software to Provide Viable Market Output

Rising internet penetration and smartphone use have resulted in exponential growth in software program users globally, needing localized versions for varied audiences. The growing internationalization of enterprises emphasizes the need for software localization, which allows companies to navigate local markets and comply with regional rules effectively. Furthermore, addressing cultural preferences and overcoming language hurdles has become critical for a consistent user experience, as consumers prefer to interact with software in their local language and cultural environment. These dynamics in the rapidly changing global software market contribute to increased demand for localized software versions.

Mobile Software Dominance to Propel Market Growth

Since most software applications are now accessed via mobile devices, mobile app localization is critical for increasing audience reach. It entails adapting the user interface and experience to fit smaller screens and optimizing for touch-based interactions. Ensuring seamless navigation and linguistic relevance on mobile platforms is crucial for effectively engaging global users. Mobile app localization is more than just translation; it includes cultural adaptation and technical improvements to improve accessibility and user happiness. This technique is critical for developers and businesses looking to tap into varied markets and provide a user-centric experience on the increasingly popular mobile device platform.

Market Restraints of the Software Localization Tools

Cost and Complexity to Restrict Market Growth

Localization is difficult and expensive, especially for large software programs. Selecting proper tools and getting qualified linguists are significant challenges. Customizing software for different cultural and language environments requires precision and specialized skills. Finding professional linguists knowledgeable about technical intricacies is critical, but it can be challenging. Furthermore, integrating appropriate localization tools and handling the complexities of large-scale projects adds to the total complexity and cost. Navigating these issues efficiently is critical for firms that want to effectively globalize their software and provide a seamless, culturally relevant experience to a varied user base.

Impact of COVID–19 on the Software Localization Tools Market

The COVID-19 epidemic posed obstacles and opportunities for the Software Localization Tools Market. The rising acceptance of remote work has resulted in increased demand for digital solutions, necessitating the development of localized software to cater to various worldwide audiences. However, supply chain interruptions, resource limits, and economic concerns impacted market growth. Customer objectives have also shifte...

Marketing Localization Service Market Outlook

The global marketing localization service market size was valued at approximately USD 4.5 billion in 2023 and is expected to reach around USD 9.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 8.5% from 2024 to 2032. The growth of this market is largely driven by the increasing need for businesses to engage with diverse global audiences through personalized and region-specific marketing strategies.

One of the key factors driving the growth of the marketing localization service market is the globalization of business operations. As more companies expand their operations across borders, the need for tailored marketing content that resonates with local cultures and languages becomes imperative. This trend is particularly prominent in industries such as e-commerce, where localized marketing strategies can significantly enhance customer engagement and conversion rates. Furthermore, technological advancements in machine translation and artificial intelligence are making localization services more efficient and cost-effective, thereby encouraging more businesses to invest in these services.

Another significant growth factor is the rising importance of customer experience in the digital age. Companies are increasingly recognizing that a one-size-fits-all approach to marketing is no longer effective in capturing the attention of global consumers. Instead, there is a growing emphasis on delivering personalized content that aligns with the cultural nuances and preferences of local markets. This shift is driving demand for a range of localization services, including translation, transcreation, copywriting, and international SEO, all of which play a crucial role in enhancing the relevance and appeal of marketing campaigns.

Moreover, the increasing penetration of the internet and social media platforms is amplifying the need for localized marketing strategies. As consumers spend more time online, they are exposed to a plethora of content from around the world. To stand out in this crowded digital landscape, companies must ensure that their marketing messages are not only linguistically accurate but also culturally relevant. This necessitates the use of professional localization services to adapt content to local tastes and preferences, thereby improving brand perception and customer loyalty.

Language Services play a pivotal role in the marketing localization service market. As businesses strive to connect with audiences across different regions, the demand for comprehensive language solutions is on the rise. These services encompass translation, interpretation, and other linguistic support that ensure marketing content is accurately conveyed in the target language. The ability to effectively communicate in multiple languages not only helps in overcoming language barriers but also enhances the cultural relevance of marketing messages. This is particularly important in today’s globalized economy, where businesses are increasingly looking to expand their reach and tap into new markets. By leveraging professional language services, companies can ensure that their marketing strategies are not only linguistically accurate but also culturally resonant, thereby improving customer engagement and brand loyalty.

Regionally, North America currently holds the largest share of the marketing localization service market, followed by Europe and Asia Pacific. The dominance of North America can be attributed to the presence of a large number of multinational corporations and a high level of digital marketing maturity. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by the rapid digitalization of economies and the growing importance of localized marketing strategies in densely populated markets such as China and India.

Service Type Analysis

The marketing localization service market can be segmented by service type into translation, transcreation, copywriting, international SEO, and others. Translation services are the most fundamental aspect of marketing localization, involving the direct conversion of content from one language to another. This segment is characterized by high demand due to its essential role in enabling businesses to communicate effectively with non-native speaking audiences. The rise of machine translation technologies, combined with human expertise, is making translation services more efficient, accurate, and cost-ef

The global translation and localization services market is experiencing robust growth, driven by the increasing globalization of businesses and the rising demand for multilingual content across various sectors. The market, estimated at $50 billion in 2025, is projected to maintain a healthy Compound Annual Growth Rate (CAGR) of 7-8% throughout the forecast period (2025-2033), reaching approximately $90 billion by 2033. This expansion is fueled by several key factors, including the rapid growth of e-commerce, the increasing adoption of multilingual websites and applications, and the growing need for localized marketing campaigns to reach diverse global audiences. Furthermore, the expansion of digital platforms and the increasing use of machine translation, while posing some challenges, are ultimately driving the demand for higher-quality human translation services for post-editing and specialized linguistic tasks. Segmentation analysis reveals that large enterprises account for a significant portion of the market, reflecting their greater resources for localization initiatives. However, the SME sector is exhibiting rapid growth, highlighting an increasing awareness and adoption of localization as a crucial strategy for global market penetration. Among the service types, document translation remains a core segment, but website and software localization are experiencing the fastest growth rates due to the exponential rise in digital content and software development. The competitive landscape is highly fragmented, with numerous players ranging from large multinational companies like RWS and TransPerfect to smaller, specialized agencies. Market leaders are consistently investing in technological advancements, strategic acquisitions, and global expansion to maintain their competitive edge. However, the entry of new players, including technology-driven startups, keeps the market dynamic and competitive. Geographical analysis shows a significant share for North America and Europe, reflecting the high concentration of multinational companies and advanced digital infrastructure. However, regions like Asia-Pacific and Latin America are demonstrating faster growth rates, presenting attractive opportunities for established and emerging players. Despite growth, the market faces some challenges, including fluctuations in global economic conditions and the need for continuous upskilling in the field to handle the increasing complexity of language and technological demands. Regulatory compliance requirements for specific industries also add another layer of complexity that requires careful consideration by service providers.

The global localization software market is experiencing robust growth, driven by the increasing need for businesses to expand their reach into international markets. The surge in global e-commerce and the rising demand for multilingual content across various platforms are key catalysts. The market is segmented by application (large enterprises and SMEs) and software type (computer-assisted translation, machine translation, and translation management software). Large enterprises are currently the dominant segment, investing heavily in sophisticated solutions to manage their global content localization needs. However, the SME segment is projected to exhibit faster growth due to the increasing accessibility and affordability of cloud-based localization software solutions. The shift towards cloud-based platforms enhances scalability, collaboration, and cost-effectiveness, attracting smaller businesses to adopt these technologies. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) are significantly improving the accuracy and efficiency of machine translation, driving market expansion. While data security and integration complexities pose challenges, the overall market outlook remains positive, with a projected sustained compound annual growth rate (CAGR) fueling significant market expansion throughout the forecast period. Competition in the market is intense, with a multitude of established players and emerging startups vying for market share. Established players like SDL Trados Studio, memoQ, and Memsource benefit from strong brand recognition and extensive feature sets. However, newer, agile companies leveraging cloud-based technologies and AI are rapidly gaining traction. Regional variations exist, with North America and Europe currently holding substantial market shares. However, the Asia-Pacific region is expected to demonstrate significant growth in the coming years due to the burgeoning economies and the increasing adoption of digital technologies in countries like India and China. The continued development of innovative features, such as improved AI-powered translation, streamlined workflows, and enhanced collaboration tools, will further shape the market landscape and cater to evolving business needs. The focus on improving the user experience and offering customized solutions will also be crucial for success in this competitive market.

InLoc is a dataset with reference 6DoF poses for large-scale indoor localization. Query photographs are captured by mobile phones at a different time than the reference 3D map, thus presenting a realistic indoor localization scenario.

Test data for the software demo of the manuscript 'Calibration-free estimation of field dependent aberrations for single molecule localization microscopy across large fields of view'. This dataset contains the first 800 frames from the 3D microtuble dataset from Figure 2 of the manuscript. It is a test dataset for the Software Demo accompanying the manuscript.

It concerns raw data for Single Molecule Localization Microscopy of microtubules of HeLa cells over a large 97 x 97 μm field of view. The images were acquired with 2 cylindrical lenses at the Fourier plane of the microscope to introduce astigmatism. The data was acquired in order to demonstrate the estimation of field dependent aberrations from single molecule localization.