Union Budget 2023: Ambitious AI initiatives on agriculture, healthcare, and sustainable cities. How can it be implemented?

Precision agriculture, often known as artificial intelligence systems, is assisting in enhancing the overall quality and accuracy of harvests. In addition, AI technology aids in the detection of pests, plant diseases, and undernutrition in farms.

The following are a few of the most exciting AI developments that are impacting the agricultural industry:

Crop and soil surveillance

Detection of insect and plant diseases

Animal health monitoring

Intelligent spraying

Mechanical weeding

Aerial mapping and surveying

Challenges

Listed below are some of the obstacles AI faces in the agriculture industry:

Farmers must understand that artificial intelligence is a more advanced data processing, gathering, and monitoring field. AI necessitates a robust technological infrastructure. Even farms equipped with some technology may fail to advance.

It is also an issue for software companies. They should begin by introducing farmers to technology through an agro-trade platform. After farmers have grown accustomed to a more straightforward solution, it will be suitable to incorporate AI functions.

Farmers may face problems due to privacy and security threats like cyberattacks and data leaks.

Farmers and agribusiness owners eager to implement innovative solutions must receive training and continuing support from corporations.

Furthermore, all problems in implementing AI in agriculture are solvable. However, for the time being, technology providers must consider three things:

How to improve their tools?

How to assist farmers in addressing their concerns?

How to readily and understandably express that machine learning helps solve genuine problems, such as lowering manual labour?

AI applications in healthcare

India has only 64 practicing doctors per 100,000 individuals, but the global average is roughly 150 per 100,000. Rural primary health centres and sub-centres are frequently understaffed and need essential infrastructure to address patient needs. In addition, it often results in the absence of high-quality diagnostic services, especially in rural India, where over 70 percent of the population resides.

The Indian government-affiliated think tank NITI Aayog is currently validating the use of AI as a screening tool in eyecare by comparing its diagnostic accuracy to that of retina specialists. In addition, NITI Aayog has been testing the application of AI in primary care for the early detection of diabetes complications. Expanding the capacity for eye exams and early detection, as well as enabling access in remote locations across the nation, is possible by integrating AI capabilities with portable screening devices like 3Nethra.

Similarly, oncology might use tools like this as well. For example, the Comprehensive Archive of Imaging, India's first de-identified cancer picture collection, was introduced by Tata Medical Center and the Indian Institute of Technology. AI-based tools can use high-quality de-identified photos to help machine-learning models find biomarkers and enhance the results of cancer research.

Also read: Airtel, Apollo Hospitals conduct 5G-based tech trial for colon cancer detection

Similarly, Microsoft's AI Network for Healthcare and Apollo Hospitals are building a machine learning model to forecast better heart attack risk in cardiovascular healthcare, a significant and rather unique challenge for India. The AI solution may uncover new risk factors and provide patients with a cardiac risk score without a thorough physical examination, enabling early illness identification, using clinical and lab data from over 400,000 patients.

The following are some of the most exciting AI advancements now impacting the healthcare industry:

Accurate Cancer Diagnosis

Early Identification of Fatal Blood Disorders

Customer Support Chatbots

Healthcare Virtual Assistants

Care for Rare Disorders

Targeted Therapy

The Automation of Duplicative Healthcare Tasks

Administration of Medical Records

Reduction in Dosing Error

Surgery Assisted by Robots

Automated Image Diagnosis

Clinical Trial Participation

Creation of New Medicines

Improved Access to Healthcare

Challenges

In adopting AI in healthcare, there needs to be more standardization. Unfortunately, there are currently no agreed-upon standards for the usage of AI in healthcare settings. This lack of standardization can be problematic for both healthcare providers and patients.

It can be challenging for healthcare providers to distinguish between effective and ineffective AI applications. It can result in wasted time and resources spent on unsuccessful AI applications. Patients may need clarification and clarity over the quality of care they receive when there is a need for more standardization. Patients may be reluctant to adopt AI applications if they lack confidence in their efficacy.

AI applications in sustainable cities

India is currently experiencing an urbanization boom. The percentage of the population living in urban areas was projected to be 31 percent in 2011; however, a recent study based on satellite data indicates that this number is already close to 45 percent and is expected to reach 60 percent by 2050, according to the document. Moreover, Unplanned urbanization is a crucial component of a country's economic progress. Still, it frequently results in congestion, over-pollution, high crime rates, and low living conditions. In addition, it may strain the infrastructure and administrative requirements of existing Indian cities.

In 2008, IBM presented smart cities as a solution to urbanization's challenges by developing a new urban environment designed for performance and growth. In a "smart city" based on the digital city's infrastructure and promising environmentally friendly architecture and cutting-edge technologies, the Internet of Things (IoT) will monitor all aspects of life. IoT creates a seamless cyber-physical landscape by connecting digital and physical cities.

The following are some of the most intriguing advances in artificial intelligence now impacting sustainable cities:

Environmental

Energy Monitoring

Traffic Administration

Waste Management

Transports publics

Parking Systems

Managing Pollution

Security

Maintenance

Anticipating Future Demands

Challenges

In general, AI networks function through surveillance cameras and sensors. This high-tech equipment necessitates a substantial expense, mainly when used for public functions. This equipment also requires routine maintenance, resulting in recurring costs. Therefore, a proper implementation plan is necessary to estimate future expenditures and optimize initial costs. Despite the seemingly high cost, AI technology improves the efficiency of smart city procedures over time. In addition, it increases income, which quickly covers the startup and operating costs.

Sometimes, natural disasters such as a hurricane might harm AI equipment placed in the open. Depending on its location and accessibility, this equipment may also be subject to theft. Moreover, these accidents would increase the cost of equipment repair or replacement. Therefore, it is vital to plan setup places so that they are both sheltered from the elements and difficult to access.

Of course, there will be obstacles, but with everyone pitching in, we can make significant progress toward these goals.