{"id":3858,"date":"2025-12-15T10:56:44","date_gmt":"2025-12-15T10:56:44","guid":{"rendered":"https:\/\/jita-au.com\/?p=3858"},"modified":"2025-12-25T12:39:45","modified_gmt":"2025-12-25T12:39:45","slug":"the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai","status":"publish","type":"post","link":"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/","title":{"rendered":"The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"3858\" class=\"elementor elementor-3858\" data-elementor-settings=\"{&quot;ha_cmc_init_switcher&quot;:&quot;no&quot;}\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-e232701 elementor-section-height-min-height elementor-section-full_width elementor-hidden-tablet elementor-hidden-mobile elementor-section-height-default elementor-section-items-middle wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no\" data-id=\"e232701\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-cb97594\" data-id=\"cb97594\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a18c791 elementor-widget__width-inherit ha-has-bg-overlay elementor-widget elementor-widget-heading\" data-id=\"a18c791\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Vol. 15 No. 2 (2025): JITA - APEIRON<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b2fff26 elementor-widget elementor-widget-heading\" data-id=\"b2fff26\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><b>Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107<b><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-52044bb elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"52044bb\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1c82606 elementor-widget elementor-widget-heading\" data-id=\"1c82606\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c297c9e elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"c297c9e\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-455c8d6 e-grid e-con-full wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no e-con e-parent\" data-id=\"455c8d6\" data-element_type=\"container\" data-settings=\"{&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-dcea8af elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"dcea8af\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Review paper<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0579899 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"0579899\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">DOI: https:\/\/doi.org\/10.7251\/JIT2502105K<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2f3b63f elementor-align-center elementor-widget elementor-widget-button\" data-id=\"2f3b63f\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/jita-au.com\/wp-content\/uploads\/2025\/12\/Pages-from-JITA_Vol-15_Issue-2-WEB-3-1.pdf\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Article PDF<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb7c4cb elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"cb7c4cb\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-61aebe3 elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"61aebe3\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data\nprocessing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies,\nfocusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported\nsensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how\nindividuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted\nusing a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience\nprojects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to\ncapture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role\nof AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis.\nAll anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub\nrepository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that\nparticipants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating\nthe highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing\nconfidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack\nof knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader\nadoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve\nenvironmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public\neducation, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5c5f19e elementor-widget elementor-widget-heading\" data-id=\"5c5f19e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4df6678 elementor-widget elementor-widget-heading\" data-id=\"4df6678\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><b>Paper received:<\/b> 31.10.2025.<br><b>Paper accepted:<\/b> 24.11.2025.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6dd494a wpr-logo-position-center elementor-widget elementor-widget-wpr-logo\" data-id=\"6dd494a\" data-element_type=\"widget\" data-widget_type=\"wpr-logo.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"wpr-logo elementor-clearfix\">\n\n\t\t\t\t\t\t\t\t<picture class=\"wpr-logo-image\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cc-by-1.png\" alt=\"\">\n\n\t\t\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\t\t\t\t\t<\/picture>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cb049d1 elementor-widget elementor-widget-shortcode\" data-id=\"cb049d1\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\"><div class=\"post-views content-post post-3858 entry-meta load-static\">\r\n\t\t\t\t<span class=\"post-views-icon dashicons dashicons-chart-bar\"><\/span> <span class=\"post-views-label\">Post Views:<\/span> <span class=\"post-views-count\">547<\/span>\r\n\t\t\t<\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-20a3f75 elementor-widget elementor-widget-shortcode\" data-id=\"20a3f75\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">Downloaded Article PDF: <span class=\"snr-download-count-num\" data-post-id=\"0\">0<\/span> times\n<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-511d0df elementor-section-height-min-height elementor-section-full_width elementor-hidden-mobile elementor-hidden-desktop elementor-hidden-laptop elementor-section-height-default elementor-section-items-middle wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no\" data-id=\"511d0df\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-0acee9c\" data-id=\"0acee9c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c0e98b3 elementor-widget__width-inherit ha-has-bg-overlay elementor-widget elementor-widget-heading\" data-id=\"c0e98b3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Vol. 15 No. 2 (2025): JITA - APEIRON<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e6b43c5 elementor-widget elementor-widget-heading\" data-id=\"e6b43c5\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><b>Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107<b><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-68f1849 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"68f1849\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-186a6b2 elementor-widget elementor-widget-heading\" data-id=\"186a6b2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7b2f501 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"7b2f501\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5027126 elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"5027126\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Review paper<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4a5312c elementor-widget__width-initial elementor-widget elementor-widget-heading\" data-id=\"4a5312c\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">DOI: https:\/\/doi.org\/10.7251\/JIT2502105K<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8d7a912 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"8d7a912\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/jita-au.com\/wp-content\/uploads\/2025\/12\/Pages-from-JITA_Vol-15_Issue-2-WEB-3-1.pdf\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Article PDF<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-580ffd3 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"580ffd3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-211717e elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"211717e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data\nprocessing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies,\nfocusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported\nsensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how\nindividuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted\nusing a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience\nprojects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to\ncapture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role\nof AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis.\nAll anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub\nrepository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that\nparticipants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating\nthe highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing\nconfidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack\nof knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader\nadoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve\nenvironmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public\neducation, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62b72c3 elementor-widget elementor-widget-heading\" data-id=\"62b72c3\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a2636dd elementor-widget elementor-widget-heading\" data-id=\"a2636dd\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><b>Paper received:<\/b> 31.10.2025.<br><b>Paper accepted:<\/b> 24.11.2025.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f4dcd16 wpr-logo-position-center elementor-widget elementor-widget-wpr-logo\" data-id=\"f4dcd16\" data-element_type=\"widget\" data-widget_type=\"wpr-logo.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"wpr-logo elementor-clearfix\">\n\n\t\t\t\t\t\t\t\t<picture class=\"wpr-logo-image\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cc-by-1.png\" alt=\"\">\n\n\t\t\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\t\t\t\t\t<\/picture>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0f73093 elementor-widget elementor-widget-shortcode\" data-id=\"0f73093\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\"><div class=\"post-views content-post post-3858 entry-meta load-static\">\r\n\t\t\t\t<span class=\"post-views-icon dashicons dashicons-chart-bar\"><\/span> <span class=\"post-views-label\">Post Views:<\/span> <span class=\"post-views-count\">547<\/span>\r\n\t\t\t<\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-975233a elementor-widget elementor-widget-shortcode\" data-id=\"975233a\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">Downloaded Article PDF: <span class=\"snr-download-count-num\" data-post-id=\"0\">0<\/span> times\n<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-2d980b8 elementor-section-height-min-height elementor-section-full_width elementor-hidden-tablet elementor-hidden-desktop elementor-hidden-laptop elementor-section-height-default elementor-section-items-middle wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no\" data-id=\"2d980b8\" data-element_type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;_ha_eqh_enable&quot;:false}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d772afa\" data-id=\"d772afa\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5597455 elementor-widget__width-inherit elementor-widget-mobile__width-inherit ha-has-bg-overlay elementor-widget elementor-widget-heading\" data-id=\"5597455\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Vol. 15 No. 2 (2025): JITA - APEIRON<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f3e70ee elementor-widget elementor-widget-heading\" data-id=\"f3e70ee\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><b>Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107<b><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b0a72e2 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"b0a72e2\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-87a3678 elementor-widget elementor-widget-heading\" data-id=\"87a3678\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96936f4 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"96936f4\" data-element_type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f04febc elementor-widget__width-initial elementor-widget-mobile__width-inherit elementor-widget elementor-widget-heading\" data-id=\"f04febc\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Review paper<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-389228b elementor-widget__width-initial elementor-widget-mobile__width-inherit elementor-widget elementor-widget-heading\" data-id=\"389228b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">DOI: https:\/\/doi.org\/10.7251\/JIT2502105K<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73b8917 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"73b8917\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/jita-au.com\/wp-content\/uploads\/2025\/12\/Pages-from-JITA_Vol-15_Issue-2-WEB-3-1.pdf\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Download Article PDF<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-80faf79 elementor-widget__width-inherit elementor-widget elementor-widget-heading\" data-id=\"80faf79\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Abstract<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8cefffd elementor-widget__width-inherit elementor-widget elementor-widget-text-editor\" data-id=\"8cefffd\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data\nprocessing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies,\nfocusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported\nsensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how\nindividuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted\nusing a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience\nprojects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to\ncapture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role\nof AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis.\nAll anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub\nrepository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that\nparticipants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating\nthe highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing\nconfidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack\nof knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader\nadoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve\nenvironmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public\neducation, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0c5e44b elementor-widget elementor-widget-heading\" data-id=\"0c5e44b\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8fcf84a elementor-widget elementor-widget-heading\" data-id=\"8fcf84a\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><b>Paper received:<\/b> 31.10.2025.<br><b>Paper accepted:<\/b> 24.11.2025.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-dee52ab wpr-logo-position-center elementor-widget elementor-widget-wpr-logo\" data-id=\"dee52ab\" data-element_type=\"widget\" data-widget_type=\"wpr-logo.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\n\t\t\t<div class=\"wpr-logo elementor-clearfix\">\n\n\t\t\t\t\t\t\t\t<picture class=\"wpr-logo-image\">\n\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/jita-au.com\/wp-content\/uploads\/2024\/03\/cc-by-1.png\" alt=\"\">\n\n\t\t\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\t\t\t\t\t<\/picture>\n\t\t\t\t\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<a class=\"wpr-logo-url\" rel=\"home\" aria-label=\"\" href=\"https:\/\/jita-au.com\/\"><\/a>\n\t\t\t\t\n\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5cb9871 elementor-widget elementor-widget-shortcode\" data-id=\"5cb9871\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\"><div class=\"post-views content-post post-3858 entry-meta load-static\">\r\n\t\t\t\t<span class=\"post-views-icon dashicons dashicons-chart-bar\"><\/span> <span class=\"post-views-label\">Post Views:<\/span> <span class=\"post-views-count\">547<\/span>\r\n\t\t\t<\/div><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-87a5ee0 elementor-widget elementor-widget-shortcode\" data-id=\"87a5ee0\" data-element_type=\"widget\" data-widget_type=\"shortcode.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-shortcode\">Downloaded Article PDF: <span class=\"snr-download-count-num\" data-post-id=\"0\">0<\/span> times\n<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System. Paper received: 31.10.2025.Paper accepted: 24.11.2025. Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System. Paper received: 31.10.2025.Paper accepted: 24.11.2025. Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence,<\/p>\n","protected":false},"author":1,"featured_media":3827,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-3858","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI - JITA -Journal of Information Technology and Application<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI - JITA -Journal of Information Technology and Application\" \/>\n<meta property=\"og:description\" content=\"Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System. Paper received: 31.10.2025.Paper accepted: 24.11.2025. Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System. Paper received: 31.10.2025.Paper accepted: 24.11.2025. Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence,\" \/>\n<meta property=\"og:url\" content=\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/\" \/>\n<meta property=\"og:site_name\" content=\"JITA -Journal of Information Technology and Application\" \/>\n<meta property=\"article:published_time\" content=\"2025-12-15T10:56:44+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-25T12:39:45+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/jita-au.com\/wp-content\/uploads\/2025\/12\/Pages-from-JITA_Vol-15_Issue-2-WEB.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"612\" \/>\n\t<meta property=\"og:image:height\" content=\"805\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/\"},\"author\":{\"name\":\"admin\",\"@id\":\"https:\/\/jita-au.com\/#\/schema\/person\/d4becda53cfcbc99c449927eabf3877f\"},\"headline\":\"The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI\",\"datePublished\":\"2025-12-15T10:56:44+00:00\",\"dateModified\":\"2025-12-25T12:39:45+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/\"},\"wordCount\":1067,\"publisher\":{\"@id\":\"https:\/\/jita-au.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/jita-au.com\/wp-content\/uploads\/2025\/12\/Pages-from-JITA_Vol-15_Issue-2-WEB.jpg\",\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/\",\"url\":\"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/\",\"name\":\"The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI - 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JITA -Journal of Information Technology and Application","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/jita-au.com\/index.php\/2025\/12\/15\/the-future-of-environmental-monitoring-citizen-science-low-cost-sensors-and-ai\/","og_locale":"en_US","og_type":"article","og_title":"The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI - JITA -Journal of Information Technology and Application","og_description":"Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System. Paper received: 31.10.2025.Paper accepted: 24.11.2025. Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. Keywords: Artificial Intelligence, Information Systems Design, System Architecture, Intelligent System. Paper received: 31.10.2025.Paper accepted: 24.11.2025. Vol. 15 No. 2 (2025): JITA &#8211; APEIRON Olja Kr\u010dadinac, Marko Markovi\u0107, \u017deljko Stankovi\u0107, Dragana \u0110oki\u0107, Vladimir \u0110oki\u0107 The Future of Environmental Monitoring: Citizen Science, Low-Cost Sensors, and AI Review paper DOI: https:\/\/doi.org\/10.7251\/JIT2502105K Download Article PDF Abstract The increasing availability of low-cost environmental sensors and the integration of Artificial Intelligence (AI) into data processing are reshaping citizen-driven environmental monitoring. This study explores public engagement with such technologies, focusing on the willingness of different population groups to participate in monitoring activities and the trust they place in AIsupported sensor data. By combining citizen science approaches with AI-assisted interpretation, the research aims to assess how individuals perceive the reliability, usefulness, and accessibility of environmental information. A quantitative survey was conducted using a 15-item online questionnaire distributed to four groups: university students, general citizens, active participants in citizenscience projects, and IT\/data professionals. The survey included multiple-choice, Likert-scale, and short open-ended questions to capture a comprehensive picture of familiarity with environmental monitoring, attitudes toward participation, and perceived role of AI in enhancing data credibility. The collected data were analyzed using descriptive statistics and comparative group analysis. All anonymized data, survey instruments, and analysis files have been made publicly available in the AIMIS-Survey-2025 GitHub repository (https:\/\/github.com\/oljak-cyber\/AIMIS-Survey-2025), ensuring reproducibility and transparency. Results indicate that participants are generally willing to engage in citizen-led monitoring, with IT and active citizen-science participants demonstrating the highest levels of trust and readiness. AI-assisted validation of sensor data was perceived as a significant factor in enhancing confidence and interpretability, particularly among technically proficient respondents. Main barriers identified included cost, lack of knowledge, and time constraints, highlighting the importance of accessible technology and educational guidance for broader adoption. Overall, the study underscores the potential of combining low-cost sensors with AI tools to empower citizens, improve environmental awareness, and generate reliable datasets for informed decision-making. Future initiatives should focus on public education, transparent AI models, and scalable sensor deployments to maximize engagement and ensure data quality. 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