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AI FOR SMART URBAN DEVELOPMENT

Thursday, July 18, 2024 - 4 min read


By analysing large datasets, AI can identify areas for improvement, predict
student outcomes, and inform educators on strategies to enhance teaching
methodologies and student outcomes.

Photo credit: Shutterstock
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By  Bitange Ndemo

Kenya’s Ambassador to Belgium


THANK YOU FOR READING BUSINESSDAILYAFRICA.COM



Show plans

Artificial Intelligence (AI) has the capacity to expedite achievement of
sustainable development goals (SDGs) in most sectors of the economy. One of the
papers contributing to the World Development Report 2024: Economic Growth in
Middle-Income Countries noted this in its findings.

The research, AI, the New Wingman of Development, noted that AI could be
leveraged for poverty reduction efforts, highlighting efficiency and
effectiveness of using it to estimate poverty statistics.

Among the significant findings in agriculture was AI's ability to assist small
farmers in increasing crop productivity in low-income countries through various
applications and solutions. It also detects crop diseases and pests, optimises
irrigation, and provides tailored crop management advice.


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It can analyse soil moisture levels, weather patterns, and crop water
requirements to conserve water and improve crop yields. AI-powered decision
support systems help farmers make informed choices about crop selection, pest
control, market trends, and resource allocation.

AI platforms can also provide real-time agricultural advice, weather forecasts,
and market information to small farmers, empowering them to improve their
farming practices.

In education, AI can facilitate the future of learning through personalised
grading and tutoring in many ways, including personalisation of learning.

Read: Positioning Kenyan livestock sector for impact investment

By tracking progress and adjusting the difficulty level of tasks, AI tutors can
provide customised learning experiences that cater to the specific needs of each
student, ensuring optimal comprehension and retention.

The study reveals that AI can offer students one-on-one tutoring and support,
supplementing traditional classroom instruction. Through interactive lessons,
practice exercises, and virtual simulations, AI tutors can engage students in
personalized learning activities that enhance their understanding of complex
concepts.

Further, AI can automate the grading process for assignments, tests, and
assessments, saving teachers time and enabling faster student feedback. AI can
use machine learning algorithms to evaluate student responses, provide scores,
and generate detailed performance reports, streamlining the grading workflow.

More importantly, AI analytics can generate valuable insights into student
performance trends, learning gaps, and instructional effectiveness.

By analysing large datasets, AI can identify areas for improvement, predict
student outcomes, and inform educators on strategies to enhance teaching
methodologies and student outcomes.

AI's role in the development sector is not limited to specific fields. It plays
a crucial role in enhancing energy efficiency, traffic management, and
infrastructure monitoring.

In terms of energy efficiency, AI algorithms can analyse energy consumption
patterns and optimise usage in various settings such as buildings, industries,
and transportation systems. Additionally, AI can predict equipment failures and
recommend maintenance schedules, thereby reducing downtime and improving overall
energy efficiency.

Moreover, AI systems can manage energy demand in real time by adjusting
consumption based on supply availability and pricing, promoting efficient energy
usage.

In traffic management, AI-powered systems are instrumental in analysing traffic
patterns, optimising signal timings, and suggesting alternative routes to
alleviate congestion and enhance traffic flow. Furthermore, AI algorithms can
predict accident-prone areas by analysing historical data, enabling the
implementation of preventive measures to bolster road safety. AI also offers
innovative parking solutions.

Regarding infrastructure monitoring, AI technologies excel in remote sensing by
analysing satellite imagery and sensor data to monitor the conditions of
critical infrastructure such as bridges, roads, and pipelines.

By detecting potential issues early on, AI helps prevent escalations and ensures
timely maintenance. AI systems also excel in asset management by tracking
infrastructure asset conditions, predicting maintenance requirements, and
optimizing resource allocation for efficient infrastructure management.

In disaster response scenarios, AI technologies prove invaluable by analyzing
real-time data to assess damage, prioritise recovery efforts, and allocate
resources effectively post-disaster.

The technology offers huge opportunities for improving urban growth and
contributing to the SDGs. However, these opportunities come with ethical and
social challenges that need to be addressed. By ensuring responsible and ethical
use of AI, we can build better and greener cities.


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