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ACHIEVING SUSTAINABLE DEVELOPMENT GOALS THROUGH BOOSTING MOBILE
CONNECTIVITY USING MACHINE LEARNING AND BIG DATA PROVIDED BY
NATIONAL TELECOM VOLUNTEERS

1
Himanshu, Sharma ; Atul, Joshi
2
1,2 Ministry of Communications, Government of India

ABSTRACT economical will replace existing solutions like drive test or
After the 5G launch in October 2022, its use cases in India MDT (Minimization of Drive Test) [3]. Recent research
have advanced significantly. The advent of 5G technology works have used deep learning models to predict mobile
holds significant promise for advancing Sustainable coverage in data sparsity conditions [4]. The performance of
Development Goals (SDGs) in India. The potential impacts numerous Machine Learning algorithms has been compared,
of 5G deployment on various aspects of sustainable and the best-suited algorithm, closest to the desired outcome,
development include focusing on economic growth, social has been recommended and used for processing data.
inclusion, environmental sustainability, and governance. As per result of the prediction, the telecom operators will
Hence, it is imperative to measure the 5G coverage evenly receive guidance regarding the necessary infrastructure or
across the country to make sure that no one is left behind to configuration adjustments, to address the gaps in telecom
benefit from development i.e. ensuring equitable justice. coverage based on the collected information.
However, there is currently no method or tool for precise 3GPP (Release 18) is beginning to embrace ML (Machine
real-time monitoring of telecom technology (2G/3G/4G/5G) Learning) capabilities as part of advanced network planning
and Quality of Service (QoS) for individuals on the ground, for future 5G deployments [5]. With the availability of
resulting in a large portion of the population without reliable geography-wise mobile network statistics, the conducive
telecom connectivity. policy to cover the uncovered areas will help to get access to
mobile to a large population and serve the purpose of
This paper proposes a methodology and tools to measure ‘Connecting the Unconnected’. As per the GSMA report [1]
ground-level QoS, which the Indian Government can use to Access to mobile products and services can provide an
take proactive steps to provide high-quality telecom important route to prosperity for individuals and well-being.
coverage to all citizens, focus on strategic areas, and achieve Most low and middle-income countries (LMICs) residents
the goals of the National Digital Communication Policy- access the internet via it. These groups can access education,
2018. The created smartphone app collects data from healthcare, and financial services via mobile devices. Mobile
volunteers using scalable server architecture. Along with phones drive innovation and economic creation, helping
signal data, topographical, meteorological, and mobile achieve the SDGs, which UN Member States approved in
tower data will be used. Machine Learning will predict 2015 under the 2030 Agenda for Sustainable Development.
coverage of places for which data is missing. The Google
map hotspot will monitor telecom coverage, and the 1.1 Current scenario for measuring mobile coverage.
dead/grey zone will be improved to increase telecom
coverage, and quality of life, and achieve SDGs. Existing solutions like MDT can certainly reduce the need
for drive tests (for measuring telecom coverage), but there
Keywords – telecommunication, quality of service, deep are still certain situations where MDT cannot replace drive
learning, received signal strength indicator, Sustainable tests [6]. Moreover, drive tests are limited in providing large-
Development. scale measurements for cities or countries [6]. As is the case
with MDT, the solution proposed in the current study can
1. INTRODUCTION assist telecom operators in coverage, mobility & capacity
As per the GSMA report, the Absence of Quality Telecom optimization, parametrization for common channels and QoS
coverage hinders the performance in achieving targets of verification [6] and hence improving the Quality of living of
Sustainable Development Goals (SDG)[1]. Further, TRAI individuals and ultimately improving SDG score of country.
data shows that rural teledensity in India is 58.24%, vs 133.7%
for urban, showing a lack of equitable justice and equal 1.2 Mobile coverage and its impact on SDGs
opportunity [2]. Poor mobile coverage leads to hindrances in improving the
The current study aims to address the issue of the Standard of life of society and some of such unfortunate
unavailability of a proprietary tool with the Govt. of India for incidents in Indian Society are cited below:
measuring telecom coverage at the ground level. In summary, a) Incidence published in [7] a child from Dapana village,
the research will develop a mobile app for volunteer citizens Morni (Oct 2020) was found sitting on a tree branch to
to install. These volunteers will periodically report their catch mobile signals to help other children complete their
technology (2G/3G/4G/5G), location, mobile phone signal homework.
strength, and other telecom parameters. This real-time and b) In another incident in New Delhi [8], a biker was killed in
historical data will be incorporated into a machine-learning the Pragati Maidan tunnel (New Delhi) as a poor signal
(ML) model to forecast signal quality in missing places delayed an emergency call for medical help (May 2023).
where no data was obtained. The solutions which initially The absence of mobile and internet connectivity directly
tested for the patch of Geographical area can be scaled to
cover the entire country and will give the Telecom coverage adversely affects the targets mentioned in SDGs, e.g.
Incidence in point (a) above hit target 4.2 of SDG- ‘By 2030,
scenario of the Nation. This solution which is scalable and

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