2. Mid-end line: Model No.: AH6676D - Successful Cases: from 2016~2019, A-MTK shipped 2,000pcs IP cameras to Taiwan Coast Guard project, and the camera has well operated during the warranty period, - Sony Starvis™ sensor is available in 2MP, 5MP resolution - Different angle lens are available. IR LED range is up to 40 meter. - Aluminum die-cast chassis with stainless steel screws. IP67 waterproof certified, IK10 vandal proof certification.

Smart Multifunctional Periodontal Pathology Quick Screening System (SMPPQSS) is the first product able to automatically identify the position of teeth and then to calculate the distribution area of dental plaque simultaneously. The system also provides a new painless gingivitis examination method that could relief examining discomfort. Neither the need of the plaque disclosing tablet nor a probe to penetrate into the patient’s periodontal pocket to determine the degree of periodontitis. Once all tooth-related data is automatically filled into the periodontal digits, the medical record sheet is uploaded to the system directly. It shortens the process to less than 10 minutes, greatly reducing the discomfort of patients during the examination as well as shortening the time doctors need to diagnose and record. SMPPQSS is easy to operate and portable. Dentists or dental assistants can check periodontal health quickly with no restriction of facilities, patients can receive a more convenient medical care even in remote rural areas or at home, or with limited mobility.

Powered by AI, this platform provides businesses with compliance management, risk intelligence analysis, and data-driven sustainable supply chain resilience, enabling them to effectively manage their supply chains.

1. Integrating data of water quality and water consumption, the online system will automatically conduct continuous data monitoring, and can be applied for both clean water and sewage water measurement. 2. Real-time monitoring: Seize real-time water information to maintain the stability of water quality and instantly react when abnormal condition is detected, dramatically increasing management efficiency. 3. Smart Dosing Scenario: Integrating automatic dosing equipments with upper and lower alarm settings to ensure dynamic stability of water quality and decrease labor cost. 4. Data Analysis: Apply schedule planning to build up the trend of historical changes and to develop the situation management model. 5. Compliance with the regulations: Complete the full-time management mode, in compliance with the regulations of the competent authority and environmental protection standards. 6. The water quality sensor (specific model) is automatically cleaned without additional consumables and can be cleaned frequently.

The Track Safety Management System is primarily aimed at addressing safety concerns along the track. It provides real-time monitoring, statistics, and detection-triggered alerts for trackside environments including stations, level crossings, along the track, and slope areas. The goal of this management system is to establish early warning alerts and prevent accidents from causing damage. Through the intelligent AIOT recognition monitoring system, it detects and analyzes station pedestrian traffic, tracks pedestrians at level crossings, identifies passing vehicles and traffic flow, detects foreign objects at level crossings and activates alarms, monitors personnel lingering and debris along the track, conducts rockfall monitoring on slopes with a rain gauge, monitors the environmental conditions in equipment boxes, and oversees the operation status of level crossing equipment. The monitoring data and image information are transmitted to the management system platform for integrated management via fiber-optic networks, NBIOT, or mobile communication. Additionally, it provides central management personnel with real-time interpretation and remote control in case of anomalies.

Live crowd movement information is crucial in busy public spaces. Manual checks and basic sensors often lack accuracy and fail to keep up with real-time changes. The People Counting System uses AI video analytics and multi-sensor fusion. It delivers accurate, real-time crowd data. The system automatically counts people, tracks direction, monitors density, and provides instant alerts and reports. Deep learning ensures accuracy in low-light or crowded conditions. Multi-target tracking prevents double-counting. Edge computing and cloud-based management enable on-site analysis and long-term monitoring. Integrating cameras, infrared, Wi-Fi, and Bluetooth data improves detection and increases coverage. The system generates real-time heat maps, flow analyses, and historical records. These support layout optimization, entry regulation, evacuation planning, and efficiency. The system serves malls, transit hubs, campuses, parks, and public buildings. It is vital for smart cities. It replaces manual counting with intelligent management for better safety, responsiveness, and adaptability.

Under the theme “Economy Next,” the Ministry of Economic Affairs presents dual pavilions on AI and net zero, illustrating Taiwan’s vision for dual transformation. The Net Zero Pavilion showcases resilient green energy systems and low-carbon supply chains, while the Industries AI Pavilion highlights advanced technologies and smart applications that delivers concrete solutions across industries in hope of fostering collaboration opportunities with global partners.

EZESG by Trade-Van Information Services Co. helps enterprises systematically complete organizational greenhouse gas (GHG) inventories in accordance with ISO 14064-1, strengthening carbon management and enhancing transparency in information disclosure. The system enables rapid establishment of an emissions source database by integrating data from energy consumption, raw materials, and operational activities. Through AI-powered OCR, it automatically identifies information from utility bills such as fuel, water, and electricity. It also incorporates Google Maps mileage calculations and taxi carbon emission models to estimate emissions from transportation activities. With built-in intelligent calculation models, the platform automatically consolidates Scope 1, Scope 2, and Scope 3 emissions data, reducing manual errors while improving data consistency and reliability. The system also supports one-click generation of GHG inventory reports and supporting documentation, simplifying procedures and shortening preparation time. Through digitalization and intelligent management, it helps enterprises respond to international regulatory requirements and steadily progress toward net-zero emissions and sustainability goals.

Delta’s EV charging solution utilizes the self-developed DeltaGrid® EVM, an electric vehicle charging management system for smart charging, power allocation, and charging equipment management. To avoid exceeding the site’s power limit during simultaneous charging, which could result in fines or power outages, the depot adopted a smart charging management system to effectively address power overuse and charging allocation issues. Under limited power conditions, the system efficiently allocates charging power for the electric buses and provides flexibility for future fleet expansion. To address the challenges of charging commercial fleets, the system has dedicated features that were developed for electric buses and commercial fleet charging needs, including Vehicle Identification, Site Current Limitation, Real-Time Alerts, etc, effectively enhances charging efficiency, optimizes operational benefits for electric fleets, and successfully demonstrates the transformation to the electrification of transportation.

With 5G private network system integration provided by Wave-In Communication, Inventec is transforming its Taoyuan Factory into a 5G smart factory, creating highly intelligent and automated production lines with AI and IoT capabilities.

Criminal and street violence cases will affect and cause panic to citizens. In order to diminish street violence cases, reducing the time to solve these cases, protecting citizens’ lives and properties, and allow citizens to live without fear, the Kaohsiung City Police Department (KCPD) built the “3D Street Violence Early Warning, AI Intelligence Collection and Integration Platform” (hereinafter called “the Platform”). The platform utilizes the Internet of Things (IoT) to combine AI image recognition and sound sensing technologies for cross-domain big data analyses. KCPD established cross-platform data interfacing and integration, mainly through “data integration” and “network analyses” to collect with the municipal government’s transportation bureaus and social bureaus; and import existing data from the KCPD data platforms. The Platform will, through web service API, (a) retrieve data built by information systems, (b) conduct big data analysis, aggregate applicable intelligence data and present it in the form of dynamic information, (c) Integrate all information and display it as maps and topologies, improve case handling efficiency. According to KCPD employees’ query, they can adjust factor weights and relationships. Analyze the results based on rational mathematical models and professional case-handling concepts, so that intelligence analysis goes beyond the limitations of platform developers and allows criminal police to maximize their capabilities.

Yunlin County Government is dedicated to establishing a human-centric smart agriculture, providing services for digital and green transformation to overcome industry challenges and climate change. People collaborate with machines, automation equipment, and computers to enhance industrial productivity by using information technology. Simultaneously, it promotes Intelligence Augmentation (IA), fostering the growth of industry personnel capabilities. To accelerate agricultural transformation, solutions are developed with experts in various fields of agriculture and livestock. Through sharing successful case studies, the aim is to guide industry stakeholders to embrace new knowledge and technologies. Additionally, counseling teams assist farmer groups in transitioning towards a smart agriculture concept that combines 'smart technology' and the 'net-zero emission' approach. The development focuses on creating a future agriculture model primarily based on automation and AI, striving for efficiency, quality, and Intelligent Automation (IA).The project won the 2024 Smart City Innovation Application Awards.