Module code and Title: EBSC7320 Masters Project Sample
Introduction
Artificial intelligence and green technology emergence has effectively aligned development of smart and sustainable towns. Technological inclusion in town has significantly influenced quality of life of residents as well as assured safety and security. However, emergence of AI and green technology becomes less dependent on human efforts, which negatively affects employment in towns.
Additionally, cyber threat is another major issue of AI-enabled services and green technology implementation. About 39% of UK organisations have identified cyber attacks after implementation of AI (GOV.UK, 2022). AI technology is most vulnerable to cyber-attacks and confidential information of local residents would be more visible and accessible to cyber criminals.
Generation of AI base automation and green technology has affected employment generation in smart towns and calculation and processing of data has dealt with by machine automation without human errors. About 1.5 million British workers are at high risk of losing jobs due to technological revolution and automation (THE GUARDIAN, 2022).
Automation threatens the job loss of most women and part-timers have lost their jobs. 25.3% of jobs disappeared between 2011 to 2017 due to the rapid development of Al and green technology implementation (ASSETS.PUBLISHING.SERVICE.GOV.UK, 2022). Hence, human-run operations are becoming lost due to smart city development with AI and green technology.
Literature Review
Significance of AI and Green Technology in Smart and Sustainable Town
Figure 1: Areas of improvement by artificial intelligence (Source: Inspired by Yigitcanlar and Cigarillo, 2020)
Insides smart cities artificial intelligence has been increasing urbanisation that aims to achieve sustainable growth. Sustainable solutions can be provided by artificial intelligence as it also provides solutions towards several challenges like administration, traffic, congestion, security surveillance and administration inside developing cities.
Important areas of improvement that can make a sustainable and green town by AI include social good, agility, stakeholders, ethics, monopoly, trust and regulation. In order to create a smart City artificial intelligence includes stakeholder engagement (Yigitcanlar and Cigarillo, 2020). Aspects of sustainability in achieving a green and smart town include achieving a common future.
Benefits influencing utilisation of AI and Green Technology in developing Smart and Sustainable Towns
Inside smart and sustainable towns there has been an implementation of security cameras that use artificial intelligence. They have an ability to analyse and evaluate footage that detects criminal behaviour in real time. There has been various emergence of new technology using artificial intelligence that also has an ability to evaluate road imagery and then further assess its issues (Pedro et al. 2019).
These specific types of technology also help in improving safety within chance when problems are unnoticed. Smart cities that include artificial technology also have an advantage to credit future needs of the people. Parking systems with the help of artificial intelligence have been creating an ability to recommend spaces depending on specific car. The artificial intelligence inside smart cities also helps in waste management by tracking recycling and further identifying what else can be recycled in specific areas.
Challenges in use of AI and Green Technology in developing Smart and Sustainable Towns
For AI capabilities availability of data along with data quality are important factors. It is highly challenging for configuring AI algorithms that control the flow of inaccurate yellow quality data. In construction of smart cities businesses can get in touch with AI professionals that can overcome challenges of implementing AI by determining the correct data set (Rejeb et al. 2022). Most developed artificial intelligence services rely on the availability of large amounts of data and algorithms.
There are high business opportunities by generation of large volumes of data but simultaneously it causes security and data storage issues. More data generation increases more users for their excess that also increases leakage of data. For construction of smart cities that can be an implementation of a data management environment for training algorithms in its applications.
An important issue that smart cities are facing is lack of citizens in participation. This can reduce a supportive environment for smart cities. One of the most significant disadvantages of implementing AI for smart and sustainable towns includes significant capital investment in technology (Regona et al. 2022).
Another disadvantage includes constant increase in electronic waste. There is a large technological gap which has been opened up between other cities and smart cities. Real estate has been becoming increasingly more expensive as it is difficult for individuals to execute and build. There is also an increasing dependence on technology service companies.
Formulation of business strategies in changing and unpredictable business environment
Implementation of AI has been creating a change in workforce by efficiently handling data management and privacy. AI has been providing advantages to business information of efficient strategies, but it also has been generating new ethical challenges for specific business.
Artificial intelligence and machine learning in the business environment has been helping companies gather data on their customers who have perceived their band (Kuleto et al. 2021). This includes artificial intelligence to scan through post the social media along with reduce and ratings that mentions a brand. Insights gain from analysis helps companies in identification of opportunities for improvement.
Another important strategy that has been created through artificial intelligence is providing product recommendations along with segmentation of audiences. Companies had been implementing artificial intelligence for recommendation of products that can align with customer’s preferences and can further keep them engaged.
Recommendation of products to artificial intelligence includes advertising departments for using AI algorithm segmentation of audiences (Haleem et al. 2022). Artificial intelligence implementation as a strategy is also used for optimisation in supply chain operations. Solutions that are given by artificial intelligence help companies to have them predict pricing of materials along with estimation and shipping regarding timing of products through a supply chain.
Theoretical Intervention
The theory of AI specifically includes development of computer systems that can perform tasks like decision making and identifications of perceptions. Development of smart cities includes sustainability for meeting human development goals. There are various theories that are related to sustainable development. One such theory includes green economy theory. Growth in employment and income are driven by private and public investment inside a green economy (Alfred, 2021).
This includes investment in various other economic activities such as assets and infrastructures allowing reduction of carbon emissions and pollution. It also prevents loss of biodiversity and ecosystem services. By targeted public expenditure green investments are required to be kept inside policy reforms and regulations.
The role of the green economy further includes sustainable use of resources and it further aims to enhance the production process. Artificial intelligence can be aligned with a green economy that helps in application of powerful capabilities of prediction for management of supply of renewable sources of energy inside smart cities. Further it can cut costs by UN necessary release of carbon.
Gap in Literature
There has been a significant gap between various cities that have not been able to make sufficient progress in the sphere of digitalisation. Further research can be conducted on increasing inequalities that create the social divide for implementation of artificial intelligence.
Artificial intelligence also had been including various other risk and challenges that create unfair buys with discrimination in decision making. Therefore, highlighting of application and implementation of AI and associated technology can be included that can further help to analyse its benefits and limitations.
Methodological Framework
Research Philosophy
Research methods select a set of principles to believe and assume which directs nature of reality in research analysis. As mentioned by Martins et al. (2018), “research philosophy” determines ways to think and behave over a collected set of data for inferred and used in research. This research has predominantly selected “interpretivism research philosophy” which is based on observation of variables over research objectives.
Alternatively, realism philosophy is based on a scientific approach to the topic and positivism carries personal opinions through experiments, which are not relevant types for this study. Interpretivism has acted to stress significance of artificial intelligence with green technology in development of smart and sustainable towns based on observation of social and cultural variables.
Research Approach
“Research approach” refers to a plan, which performs to evaluate information for a research journey. According to Ruggiano and Perry (2019), research methods use a broader plan to discuss various factors to present relevant information. “Inductive research approach” has been associated throughout this study, which has developed roles of AI and green technology for sustainable development of smart towns based on existing theories.
Deductive approach has been negated as this is based on a testing hypothesis, which has not been developed in this study. Therefore, an inductive approach has been followed throughout this study as this ensures extracting information based on existing theories.
Research Strategy
Research strategy refers to a conduction process, which helps to employ effective data collection and analysis tools. This research has employed an “archival research strategy” which has been performed to extract all possible information from secondary sources. According to Hamilton and Finley (2019), archival strategy involves engaging information from its original archives which have impactful for developing an informative study work.
All other types such as case studies, experimental, surveys and action–based strategy are involved to take an initiative for information generation, which has not been used throughout this study work. Archival strategy has helped to engage in extracting information on importance of artificial intelligence and green technology in developing smart cities and sustainable towns.
Research Choice
Research choice is needed for selecting a data type to design research work as of desired outcome. Main types of research choices are “mono-method”, “multi-method” and “mixed-method” (Nevedal et al. 2021). This study has included a mono-method, which selected one type of data collection method for a research journey. This study has chosen qualitative data types rather than quantitative data, which has successfully incorporated significant data analysis methods non-numerically and descriptively.
Data Collection
Data collection method is most vital tool in research methods, which helps to ensure data type for engaging in a research journey. Different types of data collection methods primary and secondary data collection methods, which perform to engage a specific type of data for successful completion of a study.
This research has selected a “secondary data collection method” which has incorporated pre-existed and proven information for completion of this study. Additionally, qualitative data types have ensured successful compilation of non-numeric information.
As mentioned by Chauvette et al. (2019), secondary data collection method is based on extracting information from published ones, which are mostly proven for developing the reliability of research information. “Secondary qualitative data collection method” has used reliable and authentic journals and articles, which have been published from 2018 onwards.
Additionally, “Google Scholar” database has been incorporated into selected journals and articles, which are English in language. Before 2018 published resources, all other languages except English and other data based except Google Scholar have been completely excluded in data collection, interpretation and analysis.
Data Analysis
Secondary data collection method has developed a thematic data analysis method, which has incorporated all extracting journals and articles information actively. According to Kyngäs et al. (2020), data analysis in research has a technique that helps to analyse and discuss collected data in research work. This is most important tool for data interpretation as based on analysis research outcome is predominantly dependent.
Four themes have been developed based on a total of 8 main journals and articles. Sample size of this study is 8 which are selected from secondary journals and articles designed for data analysis and interpretation in thematic data analysis method.
Ethical Consideration
This study has secured data and information based on guidelines of “Copyright, Designs and Patents Act, 1988 (c. 48)”. All included data and information has maintained current referencing system along with no manipulation act over collected information. Data in this study have provided true information by keeping its meaning the same as of its original archives.
Validity and Reliability
This study has maintained a higher level of data validity and research reliability in completion and delivery. All information is chosen from sample size, which has maintained validity of information throughout this research work. Additionally, reliable resources have been incorporated that have significantly raised research reliability.
Data Representation
Theme 1: Sustainable socio-economic development opportunities help in AI and green technology intervention in developing smart and sustainable towns
Figure 2: Sustainable socio-economic development (Source: Influenced by Yigitcanlar and Cugurullo, 2020)
Technological advancement in smart city development has assisted in increasing organised nature and better connectivity in ecosystem improvement of businesses by integration of technologies such as AI. As poised by Voda and Radu (2018), implementation of advanced technologies in real time accessibility assisted in quality improvement in services provided.
AI incorporation in information and communication systems for stimulation of economic growth opportunities helps in quality of life in urban smart cities. It was identified that over 70% of people would be living in cities by 2050 (Voda and Radu, 2018). This has effectively assisted in management of non-renewable energy management opportunities as well as reduction of wastage for developing a green smart city.
Implementation of AI in business technological development for smart cities benefits in increasing operational capabilities. In the views of Yigitcanlar and Cugurullo (2020), use of AI in urban city infrastructure assists in sustainable and autonomous smart city entities managing quality in core aspects of smart cities.
This has significantly influenced development of efficient infrastructure, actively reducing consumption of resources and decreasing carbon emission addressing environmental challenges. Further, it assist smart cities in identification of potential risks and challenges for improvement of city operation challenges, risks and creates a better smart city paradigm for enhancing life of humankind holistically.
Theme 2: Good governance and optimised cost were benefits of implementing AI and green technologies in development of sustainable and smart cities
Figure 3: Aspects of AI in good governance management (Source: Inspired by Yigitcanlar et al. 2020)
Good governance in cities assists smart cities in ensuring good governance of stakeholders in providing sustainable development opportunities for public sector. Yigitcanlar et al. (2020) asserted that integration of AI and green technologies assist smart cities in “community, technology, and policy to deliver productivity, innovation, livability, wellbeing, sustainability, accessibility, as well as good governance and planning”.
This has effectively assisted in management of a diverse range of rule based system development for businesses while addressing public domain management opportunities in urban system management. Further, integration of “robotic process automation” was implemented in projects for development of better structural management in operations of smart cities.
Incorporation advanced technologies in smart cities with AI and smart technologies have assisted in management of effective approaches for operation and cost optimisation. Use of solar energy along with sustainable transportation activities assisted in improvement of operational practices of smart cities with advanced technologies (Ghadami et al. 2021).
Optimised city planning opportunities along with reduction of costs in increasing availability of resources benefits in technological advancement opportunities in smart cities. Besides, incorporation of both short- and long-term opportunities in performance management have effectively assisted in improvement of operational strategies in operations of smart cities.
Theme 3: Increased security and unplanned population growth challenges in information management have created challenges of AI and green technology intervention in businesses.
Figure 4: Challenges in AI integration (Source: Influenced by Javed et al. 2022)
Implementation of technologies in business performance intervention including lack of effectiveness in smart city application has created issues for increasing challenges associated with data security and protection. Inefficient structuring of information from heterogeneous sources have created challenges for better performance management in smart cities (Javed et al. 2022).
Lack of utilisation of effective algorithms in implementation of AI and other technologies creates issues in development of better approaches of security management in cities. This would potentially increase issues with severe operations, financial disasters in performance improvement of businesses and cities relying on automated practices developed by AI and green technologies.
Uncontrolled or rapid urbanisation through integration of advanced technologies has created challenges for management of effective approaches in quality habitability in smart cities. Inefficiency in resource utilisation has increased challenges for smart cities with resultant effects such as “deteriorated infrastructures, poor living conditions and an unhealthy environment” (Aghimien et al. 2020).
This has effectively increased issues in maintenance of economic, political and operational challenges in smart cities as well as sustainable improvement of performance in smart cities. Lack of operational performance improvement along with ineffective or insufficient comprehensive practice management in smart cities create distress in maintaining quality of life with increasing population growth in cities.
Theme 4: Strategic planning and IoT integration recommended strategies in performance improvement of smart cities with AI and green technological intervention
Organised planning of business resources along with comprising public and private relationships of vendors have effectively assisted in improvement of operations of smart cities. As per the views of Lai et al. (2020), maintaining a standard foundation of information technology while providing support in information sharing activities have effectively assisted in implementation of advanced technologies.
Breaking down initiatives and aims of smart cities along with development of better approaches for dynamic processing help in automated devices recommended improving overall planning of smart city development. Further, environmental elements focusing on development of better approaches in quality of life management with increasing population would be necessary for improvement of operations of smart cities.
Integration of other advanced technologies along with AI in smart city infrastructure development has effectively assisted smart cities in improvement of data quality and implementation of better operational management scope. Use of IoT assists in simplification of data associated with a large amount of information when gathered from different sources about customers and businesses (Kumar et al. 2020).
Diversified structure management with IoT implementation activities have assisted in structured functionality development. This would simplify overall socio-cultural activities as well as identification of patterns in operations of smart cities. This would have potentially developed better approaches of sustainable social and economic development opportunities in development of smart cities with utilisation of better technological implementation.
Interpretation
Smart cities with strong intervention of artificial intelligence have increased sustainable growth, which facilitates administration, traffic and security surveillance in cities. As stated by Voda and Radu (2018), the implementation of AL assisted in quality improvement in city services. It has been estimated that over 70% of people would live in smart cities by 2050. This would boost renewable energy solutions in cities’ administration and domestic services.
Along with this, resource consumption and infrastructure would significantly decrease carbon emissions to reduce environmental challenges in cities. Similarly, Yigitcanlar and Cugurullo (2020) mentioned that AI in development of cities would inspire social good, agility, ethics, trust and regulation.
A strong movement towards environmental and social sustainability would be developed in such a way. Population of smart cities would be moved towards sustainability and their quality of life would be much improved with smart inclusion of technology and AI-based services.
A safer life for residences and criminal activity identified become easier with smart and sustainable city concepts. As commented by Pedro et al. (2019), AI and green technology have placed security cameras, which have developed road imagery systems to enhance social safety and security. Smart cities have included an artificial technique that is credited to the needs of people for moving towards great sustainability.
Yigitcanlar et al. (2020) included that AL and green technology are used to assist a smart city by developing technology and policy, which delivers innovation, liability, well-being and productivity. Hence, green technological inclusion and AI-enabled services in smart cities have ensured good governance and planning in smart city creation and sustainable town management.
In contrast, Javed et al. (2022) mentioned that smart city application has generated issues of data protection and security. This has been developed based on a lack of effective algorithm utilisation in AI implementation, which has affected security management in overall smart city development approach.
Data quality is most important factor in AI capabilities, which has developed several challenges for smart city sustainability. As identified by Regona et al. (2022), implementation of AI and sustainable town concept has an adverse effect on significant capital investment that is significantly more expansive and affects execution of resources.
Additionally, technological dependency has affected job market significantly as need for human efforts are reduced in this context. Green technology intervention and AI-enabled city services are rapidly moving which has affected uncontrolled and rapid urbanisation that has affected sustainability in effectively managed approaches and hampered the long-run habitability of cities. AI and green technological approaches have negatively affected resource management and job market creation, which have adversely affected economic development of cities.
An effective knowledge base and decision-making in resources management are needed to be involved in sustainability of town along with intervention of artificial intelligence and green technology. Thus, green technology and automation have to be managed in a resource-controllable and knowledgeable manner, which would significantly manage identified security and lack of employment issues.
Discussion
AI and green technologies helping in improvement of sustainable economic and operational improvement opportunities in business management have effectively assisted in improvement of operational effectiveness. However, challenges in decreasing job creation challenges in job loss create issues of significant loss of power and interest in human engagement opportunities (Lloyd and Payne, 2019).
This would create significant challenges in maintaining sustainable development opportunities for smart cities while developing organised and effective governance development. Further, ineffective policies development with technological challenges would have created issues in performing better with smart cities opportunities with AI and green technologies implementation.
Furthermore, challenges in job loss in creative industries would increase issues in maintaining uniqueness and effective occupational improvement opportunities for businesses. This would have negatively impacted on decreasing efficiencies of innovation and creativity for operational performance improvement in smart and sustainable cities. Thus, organised implementation of technologies would be necessary for job management as well as performance improvement of smart cities effectively.
Lack of proper integration of AI and green technologies have effectively increased challenges for smart cities in development of better approaches for operational improvement. In the views of Cole et al. (2019), technological and managerial complexities technological advancement increase challenges of managing security and quality in operational performance.
Additionally, multiple system and technological integration would also increase challenges for maintaining an optimised operational process opportunities in operational improvement of smart cities. High operation cost along with lack of information on organised technological integration and skill gap have also increased challenges for smart cities in sustainable development opportunities with AI and other sustainable technologies.
Ineffective computation challenges create issues for management of highest capabilities of technologies to perform. Other than this, expensive integration challenges would increase issues of wide acceptability of sustainable technologies and other advanced technologies such as AI in operational performance improvement of smart cities.
Conclusion
From above analysis, it can be concluded that AI and green technology utilisation have developed sustainability in towns and ensured a smart city approach. Automation and green technology has facilitated local services such as security and administration which has greatly impacted quality of lives of local residents. However, significant challenges are identified in uncontrollable and rapid automation in city sustainability.
Lack of effective decision-making developed capital investment over technologies has further affected resource management capability of cities. Additionally, the rapid movement of smart cities has become more of a technological dependency that has hampered sustainable economic development in cities. Additionally, data is more visible in AI-enabled devices which have affected security and privacy status of smart city concepts.
This study has collected secondary qualitative data from selected journals and articles which have ensured presentation of research data which are already tested and proven. Hence, this research has included journals and articles based on secondary information to report research objectives. Secondary data has identified significance of artificial technology and green technology that has successfully driven life-quality of residences as well as public safety and security becoming more efficient.
However, identified resource management and technological dependency challenges have affected economic and social sustainability of smart cities. Hence, it can be concluded that effective resource management and decision-making over automation and green technology are required to develop effectiveness of sustainability in smart city creation.
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Instagram Takipçi Satın Alma : Instagram, en popüler sosyal medya platformlarından biridir. Ancak, hesabınızın organik büyümesi zorlu bir süreç olabilir. Zedmedya.net olarak Instagram takipçi satın alma konusunda uzmanız. Gerçek ve aktif takipçileri uygun fiyatlarla satın alabilirsiniz. Ayrıca, hesabınızın büyümesine katkıda bulunmak için 365 gün garantili takipçi paketlerimizi de tercih edebilirsiniz. Bu sayede, Instagram hesabınızın daha hızlı bir şekilde büyümesini sağlayabilirsiniz.
Instagram 1000 Takipçi Al : Instagram hesabınızın organik büyümesini hızlandırmak için 1000 takipçi satın alabilirsiniz. Zedmedya.net olarak, Instagram 1000 takipçi almak isteyenler için gerçek ve aktif takipçileri en uygun fiyatlarla sunuyoruz. Bu sayede, hesabınızın organik büyümesine katkıda bulunabilirsiniz.
SMM Panel : SMM panel, sosyal medya hesaplarınızın büyütülmesi için kullanabileceğiniz bir araçtır. SMM panel ile, farklı sosyal medya kanalları için takipçi, beğeni, yorum ve paylaşım gibi farklı hizmetler sunulmaktadır. Zedmedya.net olarak en iyi SMM panel hizmetlerini sunuyoruz. Platformumuzda, farklı sosyal medya kanalları için en uygun fiyatlarla takipçi, beğeni, yorum ve paylaşım gibi hizmetleri satın alabilirsiniz. Ayrıca, smm panel ana sağlayıcı olarak sizlere en kaliteli hizmeti sunmayı garanti ediyoruz.
İhale teknik desteği alabileceğiniz diğer alanlarımız;
Çelik konstrüksiyon yangın merdiveni için ulaştığımız Merter Mühendislik firması gayet ekonomik ve statik açıdan dayanıklı proje çiziminden dolayı çok teşekkür ederiz.
Proje yönetimi, kararlaştırılan parametreler dahilinde proje kabul kriterlerine göre belirli proje hedeflerine ulaşmak için süreçlerin, yöntemlerin, becerilerin, bilgi ve deneyimlerin uygulanmasıdır. Proje yönetimi, sınırlı bir zaman çizelgesi ve bütçe ile sınırlı nihai çıktılara sahiptir.
Sosyal medya hesaplarınızın popülerliğini artırmak için takipçi satın alma ve benzeri teknikler son yıllarda oldukça popüler hale geldi. Özellikle TikTok ve Instagram gibi platformlarda, takipçi sayısı ve beğeni sayısı, profilinizin popülaritesini belirleyen önemli faktörlerdir.
Providerbayi.com, sosyal medya hesaplarınızın büyümesine yardımcı olmak için çeşitli hizmetler sunan bir smm panel sağlayıcısıdır. Tiktok takipçi satın al, tiktok beğeni al veya tiktok takipçi sayınızı artırmak gibi Tiktok hesabınızı büyütmek istediğinizde, Providerbayi.com’un çeşitli paket seçenekleri mevcuttur. Benzer şekilde, Instagram hesaplarınız için de birçok farklı hizmet sunuyoruz. Örneğin, 1000 takipçi satın alabilir veya 365 gün garantili takipçi hizmetimizi kullanarak hesabınızı daha da büyütebilirsiniz.
sosyal medya günümüzde işletmeler için oldukça önemli bir araç haline geldi. İşletmeler, ürünlerini ve hizmetlerini tanıtmak, müşterilerle etkileşim kurmak ve pazarlarını genişletmek için aktif bir şekilde sosyal medyayı kullanıyorlar. Bu nedenle, takipçi sayısı ve etkileşim düzeyi işletmeler için oldukça önemlidir.
Providerbayi.com, Türkiye’nin önde gelen smm panel sağlayıcılarından biridir. Sosyal medya hesaplarınızın büyümesi ve popülerlik kazanması için ihtiyacınız olan her türlü hizmeti sunar. TikTok takipçi, TikTok beğeni, Instagram takipçi gibi hizmetlerle sosyal medya hesaplarınızın etkileşimini artırabilirsiniz. Ayrıca, Instagram 1000 takipçi ve 365 gün garantili takipçi paketleri de mevcuttur.
Sosyal medya hesaplarınızın popülerliğini artırmak için takipçi satın alma ve benzeri teknikler son yıllarda oldukça popüler hale geldi. Özellikle TikTok ve Instagram gibi platformlarda, takipçi sayısı ve beğeni sayısı, profilinizin popülaritesini belirleyen önemli faktörlerdir.
Sosyal medya hesaplarınızın popülerliğini artırmak için takipçi satın alma ve benzeri teknikler son yıllarda oldukça popüler hale geldi. Özellikle TikTok ve Instagram gibi platformlarda, takipçi sayısı ve beğeni sayısı, profilinizin popülaritesini belirleyen önemli faktörlerdir.
Takipçi satın al: Sosyal medya hesaplarınızın popülerliğini artırmak için tercih edilen bir yöntemdir. Ancak, organik takipçi kazanmak için kaliteli içerikler paylaşmanız daha önemlidir.
SMM Panel : SMM panel, sosyal medya hesaplarınızın büyütülmesi için kullanabileceğiniz bir araçtır. SMM panel ile, farklı sosyal medya kanalları için takipçi, beğeni, yorum ve paylaşım gibi farklı hizmetler sunulmaktadır. Zedmedya.net olarak en iyi SMM panel hizmetlerini sunuyoruz. Platformumuzda, farklı sosyal medya kanalları için en uygun fiyatlarla takipçi, beğeni, yorum ve paylaşım gibi hizmetleri satın alabilirsiniz. Ayrıca, smm panel ana sağlayıcı olarak sizlere en kaliteli hizmeti sunmayı garanti ediyoruz.
Instagram Takipçi Satın Alma : Instagram, en popüler sosyal medya platformlarından biridir. Ancak, hesabınızın organik büyümesi zorlu bir süreç olabilir. Zedmedya.net olarak Instagram takipçi satın alma konusunda uzmanız. Gerçek ve aktif takipçileri uygun fiyatlarla satın alabilirsiniz. Ayrıca, hesabınızın büyümesine katkıda bulunmak için 365 gün garantili takipçi paketlerimizi de tercih edebilirsiniz. Bu sayede, Instagram hesabınızın daha hızlı bir şekilde büyümesini sağlayabilirsiniz.
Instagram 1000 Takipçi Al : Instagram hesabınızın organik büyümesini hızlandırmak için 1000 takipçi satın alabilirsiniz. Zedmedya.net olarak, Instagram 1000 takipçi almak isteyenler için gerçek ve aktif takipçileri en uygun fiyatlarla sunuyoruz. Bu sayede, hesabınızın organik büyümesine katkıda bulunabilirsiniz.
SMM Panel : SMM panel, sosyal medya hesaplarınızın büyütülmesi için kullanabileceğiniz bir araçtır. SMM panel ile, farklı sosyal medya kanalları için takipçi, beğeni, yorum ve paylaşım gibi farklı hizmetler sunulmaktadır. Zedmedya.net olarak en iyi SMM panel hizmetlerini sunuyoruz. Platformumuzda, farklı sosyal medya kanalları için en uygun fiyatlarla takipçi, beğeni, yorum ve paylaşım gibi hizmetleri satın alabilirsiniz. Ayrıca, smm panel ana sağlayıcı olarak sizlere en kaliteli hizmeti sunmayı garanti ediyoruz.