Misr University for Science & Technology
Faculty of Information Technology
IS402-Assignment 2
Student Name:
Student ID:
Section CRN:
Fall 2022-2023
Mobile app using AI:
Hello genius
Hello Genius is an app-based learning system that connects parents and children
through personalized learning experiences headquartered in San Francisco Bay Area,
West Coast, Western US founded by Jack Lee, and Lee Daley. It is a kid’s learning app
full of captivating videos, photos, books, and interactive features that children love to
explore. It provides an easy way to make learning fun. It helps reveal your child’s
interests, strengths, and passions. It’s not made to replace conventional curriculums,
but the insights might benefit teachers who want to better understand your child.
Hello Genius uniquely enables parents to bond with and inspire children across the
dinner table or the world. Never miss a moment to learn and connect with your kids,
even through busy work schedules and business trips. The parenting bond is key to a
child’s confidence, resilience, and happiness. Equally, we believe parents should be as
free from anxiety as possible and we want to offer tools to make them as connected
and enriched as possible, even when work and the demands of life mean long hours
away from their children.
founded on the philosophy of Sir Ken Robinson
Sir Ken Robinson, Ph.D. was a world-leading figure on child creativity and human
potential. He believed education should encourage our children's natural curiosity,
creativity, and
imagination
and
focus less on
standardized
curriculums, leaning
instead to approaches that support each child’s individuality and unique talents.
The AI of Hello Genius represents a tremendous leap in learning technology.
Everything your child chooses to read and see tells us a little more about their
interests and the kinds of topics that motivate them to learn. Hello Genius is actively
using 30 technologies for its website, according to BuiltWith. These include Viewport
Meta, iPhone / Mobile Compatible, and Google Font API. It has a recommendation
system that suggests information on related topics and connects new information
back to what children already know. Moreover, it is featuring advanced voice
recognition technology and sophisticated algorithms, as it allows children to search by
voice or text and serves up a diverse range of media types. Furthermore, it uses object
detection to detect objects from a photo that is uploaded by the child and gives
children information about each object[1].
Mobile App using IoT:
KDDI Japan on Mount Fuji – Tracking Traffic and Weather Conditions
Each of the starting points for an ascent of Mount Fuji has an IoT sensor installed that
measures the temperature, humidity, and the number of people passing through that
location. After that, KDDI makes that data accessible online so climbers may
organize their schedules, clothes, and equipment. Additionally, the municipalities can
use this data to enhance the paths and other facilities close to the mountain. For
instance, the answer showed that around 80% of the visitors prefer to walk along the
nearby hiking trail without climbing to the summit. In response, KDDI equipped the
trail centre with virtual reality technology that allows users to experience dynamic
360-degree views as they begin their ascent to the summit. When the service first
debuted in 2017, KDDI enabled it for the first time via LoRa connectivity. To cut
expenses and increase coverage, it switched to LTE-M for the 2018 campaign.
Smartphones and personal PCs can display the data collected by mountain sensors.
In addition to mountaineering, KDDI predicts that low power wide area networking
will transform how people participate in a variety of other leisure activities, including
surfing, music festivals, and other events. Connected sensors, like those on Mount
Fuji, may be used to measure the magnitude of waves, count the number of shoppers
in an aisle, or keep track of the number of vehicles driving up to a festival or tourist
destination, among other things. An event or site manager may be able to monitor
congestion levels in real time and take appropriate action using the data gathered by
these sensors.
KDDI confirmed nationwide coverage in June 2018 after first launching its LTE-M
commercial network in Japan's northeast in January 2018. It claims that LTE-M will be
essential in providing IoT services for its clients. Through a web interface that can
track traffic levels, payment information, connectivity status, and other information,
KDDI offers SIM management services to IoT customers. KDDI charges JPY 40
(US$0.37) per month per SIM for large volume deployments involving more than five
million LTE-M subscriptions, compared to JPY 100 (US$1) per month (per SIM) for a
single subscription (in both cases if the monthly usage needs to be 10 KB or less). In an
effort to deliver a one-stop IoT solution covering everything from connected sensors
to the analysis and use of data, the operator can also offer data analytics through a
joint venture with Accenture. Keigo Harada, General Manager and Head of the IoT
Business Planning Department at KDDI, says, “We aim to become business partners
for our customers, solving their business challenges, rather than following the
traditional product-led business model,”. KDDI believes that low power wide area
connection has the ability to assist a variety of use cases, including telematics, smart
meters,
remote
industrial
equipment
monitoring,
building
infrastructure
and
agriculture, vehicle tracking and management, delivery and logistics, and security. The
operator thinks mobile IoT technology might be used to monitor people's physical
health, such as by identifying symptoms of heat stroke. For example, to facilitate finegrained water level monitoring for the crops, KDDI placed LTE-M capable sensors in
paddy fields. By employing LTE-M to gather information from water level sensors in
the paddy fields, the Toyooka City Smart Agriculture Project enables farmers to
monitor the growing environment from a PC and smartphone[2].
Mobile App using Big Data:
Roambi
The rush toward data-driven decision-making frequently overlooks mobility. More
sophisticated data manipulation methods are required for today's increasingly mobile
workforces than only the standard business tools that are frequently condensed for
mobile. Mobile workers need the ability to access and analyze the same business data
they use in the office in order to make smart, on-the-go decisions.
Roambi claims that this issue was the reason it was created. Roambi wants to
reimagine the mobile business app to boost mobile workers' productivity and
decision-making. From a fully mobile perspective, Roambi redesigns how people
interact with, share, and present data[3].
For mobile users, Roambi offers data visualization. With the help of Roambi's
Analytics, data gathered from various sources is transformed into an easy-to-use
experience that helps users better understand the meaning of the data and how it
may impact the company's operations. Roambi Analytics is made up of 10 dynamic,
integrated visualizations, called "VIEWS," as opposed to static dashboards. These
views make it simpler for users to navigate and display all of the data in one area.
Roambi offers 100% Offline Functionality for Mobile and PC, Native Applications,
Instantaneous
Performance
with
NO
SPINNERS,
and
Beautiful,
Integrated
Visualizations. Use Roambi on computers as well as mobile devices. Roambi's
Analytics includes Blink, which makes it simple to integrate CSV files with mobile
devices like iPhones and iPads. Utilize personal devices to manage all information and
maintain access even when not in the workspace. Roambi Flow is another great
feature that let users create multi-touch publications that not only show analytics
data but also be able to customize it together with videos, images, and other
interesting content. This also promotes better experience and establishes better
connections with the company's leads[4].
References
[1] https://www.hellogenius.com/
[2] Mobile IoT Case Study: How Asia Pacific Intelligently Connects to IoT, GSMA,
February 2019.
[3] Jeff Vance, 5 Big Data Apps with Effective Use Cases, July 24, 2014,
https://www.datamation.com/applications/5-big-data-apps-with-effective-use-cases/
[4] Roambi Analytics Review, PAT Research
https://www.predictiveanalyticstoday.com/roambi-analytics/