A Smart City Operations Center is a central control point used to manage various services, infrastructure and security in a city. It monitors, analyzes and manages various systems in the city using a range of sensors and other smart technology

The Smart City Operations Center includes a number of important components:

Data Collection Systems: Collects various types of data through sensors, cameras and other devices throughout the city. This data includes traffic flow, weather, energy consumption, environmental conditions and other safety-related information.

Data Analysis and Integration: The collected data is analyzed and integrated in a centralized system. This is important for understanding and optimizing the interaction between various systems in the city.

Decision Support Systems: In the operations center, city managers and operators make informed decisions using data analytics and reports. These decisions include strategic planning for traffic management, emergency responses, energy efficiency and other city services.

Security and Emergency Management: The Smart City Operations Center is used to monitor security threats and manage emergency responses. Cameras, sensors and other data sources continuously assess the security situation in the city.

Public Outreach and Information: Smart city operations centers are used to share and interact with information for city residents. This includes daily information such as traffic status, events, weather alerts, etc.

This type of operations center aims to improve the quality of life in the city, support sustainability and ensure safety by providing better visibility and control to the city government.

The International Smart City Roadmap & Certification describes the roadmap and certification processes used to measure the performance of sustainable and smart cities. The standard includes indicators across 19 key smart city components that have been identified to assess various aspects of a city, particularly its performance in critical areas such as infrastructure, energy, transportation, education, health, safety and security. The International Smart City Roadmap and Certification includes the following steps:

• Assessment and Planning: Assessing the current state of the city and setting smart city targets.
• Indicator Identification: Identifying indicators in accordance with ISO 37120 etc. standards. These indicators are used to measure the city's performance in specific areas.
• Infrastructure and Technology Development: Implementation of plans and projects to develop smart city technologies and infrastructure.
• Data Collection and Analysis: Establish regular data collection and analysis processes for the identified indicators.
• Monitoring and Evaluation: Monitoring and evaluation of city performance at regular intervals.
• Certification Application: After meeting the necessary requirements, applying for International Smart City certification.
• Certification Audit: Conducting compliance audits and verifying compliance with standards.
• Obtaining Certification: Management of the application processes and official certification of the smart city's compliance with an international standard by relevant organizations.

AI-supported disaster management refers to solutions that involve the use of artificial intelligence technologies in the process of coping with disasters. Our technologies in this field are designed to support objectives such as rapid response, effective management and efficient use of resources in disaster situations. Our Artificial Intelligence Supported Disaster Management application has features that will guide many topics, especially "Risk Analysis and Prediction, Early Warning Systems, Evacuation and Road Management, Retrospective Analysis and Learning, Emergency Management and Coordination, Post-Disaster Recovery". In addition, the use of these applications brings important issues such as ethics, security and privacy. We always use our technology in accordance with ethical standards and legal regulations.

Smart energy management refers to an approach that uses technology and automation to optimize energy consumption, use resources more effectively and improve energy efficiency. These systems are often applied in various fields such as building management, industrial facilities and grid infrastructure. The key components of smart energy management are;

Data Collection and Analysis: Smart energy management collects energy consumption, production and other relevant data through sensors and meters. This data is monitored and analyzed in real time.

Automation and Control Systems: Advanced control systems use automation technologies to optimize energy use. Energy-consuming devices such as lighting, heating, ventilation and cooling systems operate more efficiently with demand management and timed control.

Energy Storage and Renewable Resources: Smart energy management integrates sustainable solutions such as energy storage systems and renewable energy sources. This means balancing energy sources, maximizing energy from renewable sources such as solar or wind, and increasing the ability to operate off-grid.

Energy Efficiency and Awareness: Users and system administrators are made aware with information on energy consumption and stimulated to improve energy efficiency. This enables more informed decisions to be made to save energy.

Remote Monitoring and Management: Smart energy management systems often have remote monitoring and management features. This enables remote access to control, update and optimize systems remotely.

As a result, smart energy management is a strategy that aims to reduce energy costs, minimize environmental impacts and make energy use more sustainable.

Smart water management refers to an approach that incorporates technology and data analytics to use water resources more effectively and sustainably. This system integrates various technologies to monitor, analyze and optimize water consumption.

Sensor and Data Collection: Smart water management uses sensors to monitor and manage water resources. Through these sensors, important information such as water levels, water quality, water pressures and consumption data are collected.

Remote Monitoring and Control: Water management systems have remote monitoring and control capabilities. This allows for more effective management of resources by monitoring water resources remotely and controlling them when necessary.

Data Analysis and Forecasting: The collected data is analyzed through specialized software or AI-based analytical tools. These analyses are used to understand water consumption patterns, predict future demands and optimize the use of water resources.

Smart Irrigation Systems: Smart water management in agriculture integrates sensors and automated irrigation systems. By monitoring soil moisture levels and using weather forecasts, it ensures that water is used in the right amounts and at the right times.

Water Leak Detection: Smart water management minimizes water losses by using sensors for water leak detection. In this way, water resources are used more efficiently and losses are prevented.

Smart water management promotes sustainable water use, ensures efficient use of water resources and makes water management more effective and environmentally friendly. These systems play an important role in combating water crises and protecting water resources for future generations.

Today, with the rapid advancement of technology, the transportation sector is undergoing significant transformations and the concept of intelligent transportation management has entered our lives. Intelligent transportation aims to provide more effective and sustainable solutions to issues such as traffic, public transportation and parking management in cities through the integration of data analytics, sensor technology and other smart systems.

The Intelligent Transportation System uses smart sensors to monitor traffic density, analyze instant data and provide real-time information to drivers and passengers. It also integrates data analytics and artificial intelligence algorithms to optimize the routes of public transport vehicles, regulate traffic flow and use parking spaces more effectively.

The benefits of smart transportation include reducing traffic congestion, increasing energy efficiency, lowering carbon emissions and improving the overall transportation infrastructure of cities. It improves the travel experience of passengers while enabling city governments to make better data-driven decisions.

In conclusion, intelligent transportation management is an important technological development that facilitates the daily lives of people living in modern cities and makes urban life more sustainable. With the widespread use of these systems, cities will be able to respond more effectively to the transportation needs of the future and have a smarter transportation infrastructure.

Smart environmental management refers to an approach that aims to use natural resources more efficiently and sustainably through the integration of various technological solutions and information systems. In this context, technologies such as various sensors, data analytics, artificial intelligence, and IoT (Internet of Things) are used to monitor, analyze and control environmental factors.

Smart environmental management is applied in areas such as energy saving, waste management, effective use of water resources, and monitoring air quality. Environmental data is collected through sensors and by analyzing this data, it is possible to monitor various environmental parameters. This information is used to assist decision makers in formulating and implementing environmental policies.

Smart environmental management is emerging as an important strategy for cities, industries and communities to achieve sustainability goals, reduce environmental impacts and conserve natural resources. This approach enables the development and implementation of environmentally friendly practices using the power of technology.