Using AI to track bird migration

On hearing the first cuckoo of spring, the poet’s heart might sing, and while one swallow does not a summer make, the annual migrations of bird species across continents have fascinated us for centuries. Today, however, technology is giving ornithologists the means to follow these incredible journeys in ways that would have been unimaginable to earlier generations of naturalists.

Research in the International Journal of Global Environmental Issues shows that artificial intelligence (AI) is being used by conservationists to help predict bird migration timings and patterns. The technology might allow them to identify how climate change and habitat loss are affecting the journeys of many migratory bird species.

The team looked at research into machine learning and deep learning models used to analyse migration, habitat preferences, and bird populations. They explain that machine learning refers to computer systems that identify patterns in data, while deep learning is a form of machine learning that uses layered neural networks to detect more complex patterns. Increasingly, automated sound recording devices that pick up bird calls and songs as they migrate overhead are providing useful data where visual monitoring is simply not possible.

These remote monitoring systems can operate for long periods with relatively little human intervention, building up a picture of migration activity over many nights, seasons, and even years. They offer researchers a way to monitor birds at a scale that would be extremely difficult to achieve with conventional field observations. This technology could thus strengthen monitoring, as habitats and migration routes respond to rising temperatures, changing rainfall, and land development. More accurate forecasts will help determine which habitats require greater protection and inform policy to ensure migratory bird conservation remains central to climate adaptation strategies.

Musale, P.P. and Sonawani, S.S. (2026) ‘Advancements and challenges in bird migration models: a comprehensive survey’, Int. J. Global Environmental Issues, Vol. 25, No. 1, pp.1–26.

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Masking for a friend

A face-recognition system that can see who you are even if you're wearing a face mask covering nose and mouth is discussed in the International Journal of Computational Vision and Robotics. The new system uses biometrics from around the eyes and forehead.

The research addresses a weakness in face recognition as a technology that was exposed during the pandemic. During that period when masks were often compulsory, their use caused conventional face-recognition systems to reject some authorised users. Unlike iris recognition, which can require specialised near-infrared imaging and controlled conditions, periocular recognition can operate with ordinary visible-light cameras.

The team has combined several types of visual information. First, a deep-learning model extracts features from around the eyes. Secondly, two image-processing techniques, local binary patterns and histograms of orientated gradients, analyse the person's forehead. The approach then combines the data to identify or verify an individual with an accuracy up to about 96 per cent in tests on one database but rather less on other testbeds.

Given that, the approach might be used as an initial screening step rather than as definitive proof of identity. A facial match could prompt further authentication with a second factor such as a password, PIN or security token. However, the team explains that they should be able to add other feature recognition into the same system, ears, face shape or profile, and those should improve performance significantly.

Agarwal, D. and Bansal, A. (2026) 'Fusion of periocular and forehead features for masked face recognition', Int. J. Computational Vision and Robotics, Vol. 17, No. 2, pp.133-158.

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Don’t have me phubbing on the telephone

Personality traits may help predict whether a person will ignore others while using their smartphones, according to a study of healthcare workers in the International Journal of Business Innovation and Research.

The study involved 177 co-workers and looked at how prevalent “phubbing” is. Phubbing is a portmanteau of the words 'phone' and 'snub' and is the practice of ignoring someone in preference to using one’s phone despite being in a situation in which face-to-face conversation and interaction would be the norm. The study might help social scientists and others understand better the notion of smartphone addiction.

The research assessed participants using the so-called Big Five personality traits - openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism. Personality and phone addiction were self-reported, while co-workers provided evidence of phubbing by others. The team found that people scoring higher in openness, extraversion and neuroticism were more likely to display phubbing behaviour. Conscientiousness, a tendency towards responsibility, self-discipline, and consideration of one’s obligations, was associated with less phubbing. There was no significant relationship between phubbing and agreeableness, oddly enough.

If a condition we might call mobile phone addiction exists, then it might be described as an inability to refrain from phone use despite the potential for offline human interaction. To be a true addiction, there has to be associated harm, and the researchers suggest that psychological harm may well occur, either to the phubber or the phubbed. This phenomenon partly explains the relationships between personality and phubbing, the team reports. That said, the researchers emphasise that understanding individual differences behind problematic smartphone use could help organisations address antisocial phone behaviour without treating smartphone use itself as inherently harmful.

Khan, M.N., Shahzad, K. and Shafi, M.Q. (2026) ‘This or that, which coworker phubb more; association between personality traits and phubbing behaviour through mobile phone addiction’, Int. J. Business Innovation and Research, Vol. 40, No. 4, pp.466–487.

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Workplace social media reduces staff turnover

Social media used inside organisations may help engage employees and increase staff retention, according to a paper in the International Journal of Applied Systemic Studies, which looked at this phenomenon in China. Employee engagement refers to a worker’s emotional and motivational connection with their organisation, the team explains, while retention is the organisation’s ability to keep employees and reduce staff turnover rates.

The researchers used a statistical method known as structural equation modelling to test the relationships between various factors. They considered whether an employee’s perception of technology affected their working relationship. Indeed, perceived ease of use and perceived usefulness strengthened the impact of social media technology on engagement and retention.

The findings are particularly relevant to China, where social media platforms are important workplace communication channels. The distinctive cultural and regulatory environment there provided the researchers with a useful setting for studying digital employment practices.

Social media, the team points out, can facilitate communication, knowledge sharing, and recognition. It can thus help employees feel more connected to colleagues, their superiors, and the organisation in general. If this improves employee retention, then it has the benefit to the organisation of keeping hold of experienced and talented staff and reducing recruitment and training costs.

However, the study shows that introducing social media tools may not be sufficient for optimal employee engagement and retention. The team explains that organisations need to ensure employees find these tools easy to use and patently useful.

Liu, J. (2026) ‘Social media as a tool for employee engagement and retention: moderation of perceived ease of use and usefulness’, Int. J. Applied Systemic Studies, Vol. 13, No. 3, pp.220–236.

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The internet of bodies and cultural tourism

Research in the International Journal of Arts and Technology monitored electrical brain activity and heart rate in people watching patriotically themed Chinese films. They found that the main incidental music in such films can increase the positive emotional response and patriotic sentiment in the audience and at the same time reduce negative emotional responses.

The findings could be used by film-makers offering content in the context of tourism, specifically cultural tourism. Such insights have potential in boosting the impact of film-themed attractions, reconstructed locations, tourism and educational programmes. The researchers add that their approach essentially uses the “internet of bodies”, a human analogue of the “internet of things”, in which technologies collect and analyse data about human behaviour and physiological states. In the cultural tourism setting, this technology would combine information gathered while people watch films with data on their behaviour and interactions at related physical sites.

The extension into social media interactions might also be used to amplify emotional responses through discussion and engagement beyond the film itself.

The approach does raise ethical questions about how physiological and behavioural data should be collected and used when technologies designed to measure audience responses become part of cultural experiences. It might be that prior consent of audience members should be necessary before anyone is subsumed into an internet of bodies system, and individuals should have the ability to opt out.

Wen, L., Sun, W. and Ding, R. (2026) ‘Neuroscientific effects of main melody films on audience patriotic sentiment in the context of culture tourism integration: an IoB perspective’, Int. J. Arts and Technology, Vol. 16, No. 9, pp.45–64.

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International Journal of Intelligent Information and Database Systems is now an open access-only journal

Inderscience's Editorial Office is pleased to announce that the International Journal of Intelligent Information and Database Systems is now an Open Access-only journal. All accepted articles submitted from 24 August 2026 onwards will be Open Access, and will require an article processing charge of EUR €1700.

International Journal of International Journal of Metadata, Semantics and Ontologies is now an open access-only journal

We are pleased to announce that the International Journal of Metadata, Semantics and Ontologies is now an Open Access-only journal. All accepted articles submitted from 24 August 2026 onwards will be Open Access, and will require an article processing charge of EUR €1700.

Such a lovely place, but so many leave

Research published in the International Journal of Environment and Sustainable Development analysed interviews with over 300 Chinese hotel interns to see how perceptions regarding hotel work affect whether graduates pursue a career in the industry or not. The findings suggest that negative perceptions do indeed deter graduate interns from pursuing hospitality as a career.

Fundamentally, the team found that occupational stigma, the belief that a profession has low status or is undesirable, was most associated with weaker professional identity. Those graduates with this perception generally did not choose hotel work as a career.

The findings highlight a significant recruitment problem for China’s hotel industry. Despite its reliance on a large and stable workforce, only an estimated 10 to 20 per cent of graduates in hospitality and tourism enter the sector. Moreover, internships, which are intended to provide graduates with practical experience early in their career, sometimes reinforce negative perceptions and lead to many graduates dropping out of the sector before they have even taken more than a few tentative steps on this career path.

The study did find that vocational skills sometimes offset the stigma. Interns with additional skills were less affected by negative perceptions of the industry. This suggests that practical training and professional certification might boost confidence in hotel careers and improve professional identity in the sector.

Yu, F., Liu, L. and Zuo, Z. (2026) ‘Hotel interns’ career choice intentions from a high-versus-low climate changing region background’, Int. J. Environment and Sustainable Development, Vol. 25, No. 7, pp.64–83.

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Research pick: Lowering the scenic language barrier - "Multimedia artificial intelligence technology for accurate translation of scenic area public notices from Chinese to English in ecological translation studies"

A new artificial intelligence, or AI, translation model could improve the accuracy and cultural appropriateness of Chinese-English public signs in tourist attractions, according to research in the International Journal of Environmental Technology and Management. The approach treats translation as more than a word-for-word conversion and combines machine translation with principles from eco-translatology in which language, culture, and social context are considered.

The researchers have incorporated these principles into a neural translation system based on transformer architecture, a widely used AI system for processing relationships between words in a sentence. The model thus uses cultural-language databases together with sentiment analysis. The latter uses a computer to assess the emotional or evaluative language in a piece of text. The system can then tweak the translation for linguistic, cultural, and communicative context.

In tests, the team reports an improvement over older approaches for cultural adaptability, fluency, and completeness. The findings suggest that translation systems designed for specific functions may be better suited to public-facing texts where a culturally inappropriate phrase might confuse visitors or change the intended message. The same system could support multilingual urban signs, heritage-site interpretation, and educational notices.

At this time, the model is limited to a single language pair and a corpus concentrated on Chinese scenic areas. However, the researchers plan to expand the training data and incorporate knowledge graphs, situational modelling, and causal reasoning to improve the system’s ability to be used in different cultures and settings. There is also the potential to improve the handling of historical references, deeper cultural meanings, and linguistic variation by developing deeper reasoning rather than relying on simple rules and templates.

Zhang, C. and Wang, Y. (2026) ‘Multimedia artificial intelligence technology for accurate translation of scenic area public notices from Chinese to English in ecological translation studies’, Int. J. Environmental Technology and Management, Vol. 29, No. 7, pp.1–22.

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Prof. Hai Zhao appointed as new Editor in Chief of International Journal of Signal and Imaging Systems Engineering

Prof. Hai Zhao from Northeastern University in China has been appointed to take over editorship of the International Journal of Signal and Imaging Systems Engineering.