scholarly journals Automatic delivery-scam prevention using Raspberry-Pi

2022 ◽  
Vol 25 (1) ◽  
pp. 113
Author(s):  
Bindu Bhaskaran ◽  
Barath Krishna Gunasekaran ◽  
Srinivasan Velumani
Keyword(s):  
Pi Controller ◽  
Raspberry Pi ◽  
Prevention System ◽  
Product Delivery ◽  
Time Reduction

The word ‘automatic’ is unavoidable in this modern technical era. Automation facilitates not only technical advancement and time reduction to several processes, but also provides protection in various aspects. Delivery scam is a commonly occurring crime and it has to be reduced. Product delivery is a long process which involves various people to ensure correct delivery to the customer, providing chances for scam to occur. This paper discusses on an automatic delivery-scam prevention system with the help of Raspberry-Pi controller. This system provides safety to the ordered goods by limiting the authorisation of opening the packages to company and the customer only. It assures the safe and correct delivery of the ordered product.

Monitoring Biosensors and Obtaining Data Using GSM Module

2016 ◽  
Vol 5 (2) ◽  
pp. 86
Author(s):  
Hemavathy RM
Keyword(s):  
Control System ◽  
Oxygen Supply ◽  
Human Life ◽  
Pi Controller ◽  
Raspberry Pi ◽  
Monitoring Systems ◽  
Memory Location ◽  
Coverage Area ◽  
Standard Data ◽  
Wireless Node

<p>The main focus of the project is to prevent the loss of human life against the discomfort and death caused by the lack of attention towards the patients due to the improper monitoring systems provided in the hospital. The aim of the project is to monitor the bio sensors attached to the persons in their body either internally or externally. The biosensors which are about to be used in this project are EEG sensor (electro encephalogram sensor). An ECG sensor (electro cardiogram sensor) which is very essential for a critical patient, this project also emphasizes on the extended design of a special type of sensor called the oxygen insensitive microscale biosensor which helps in the monitoring of constant oxygen supply in blood thereby detecting blood cancer at the earliest stage. The data from all the sensors are sent to a central wireless node through wifi. From the main node the data is sent to the control station of the hospital through zigbee as the coverage area of certain hospitals is more than the coverage area of a Bluetooth. The control station segregates the data of different patients and stores in the memory location. If any of the patient data exceeds the standard data fed to the control station by the doctor then a message will be sent to the mobile of the attendee and the doctor using the GSM control system.<em></em></p><p><em>Keywords: Biosensors, Raspberry pi (controller), GSM, Zigbee</em></p><p><em> </em></p>

scholarly journals IoT based Raspberry Pi Crop Vandalism Prevention system

2019 ◽  
Vol 9 (1) ◽  
pp. 3188-3192 ◽  
Keyword(s):  
Soil Moisture ◽  
Food Production ◽  
Irrigation System ◽  
Protection System ◽  
Population Increase ◽  
Raspberry Pi ◽  
Agricultural Fields ◽  
Important Process ◽  
Prevention System ◽  
Automated Irrigation System

Agriculture is a major source of food production in our country. Growth in population increase the demand for food production and agriculture is the main source. Irrigation in agriculture is an important process that affects the development of crops. In particular, farmers visit their agricultural fields regularly to check the level of soil moisture and water is pumped by motors to irrigate their respective fields on the basis of requirements. But the limitation of protecting crops from animals becomes a major concern for yield. This works presents the protection system in addition to the automated irrigation system.

scholarly journals Global industrial process monitoring using raspberry pi controller

2017 ◽  
Vol 6 (5) ◽  
pp. 3623-3627
Author(s):  
Sayali Gajanan Desai ◽  
◽  
B. T. Salokhe ◽  
A. S. Mali ◽  
◽  
...  
Keyword(s):  
Process Monitoring ◽  
Industrial Process ◽  
Pi Controller ◽  
Raspberry Pi

scholarly journals IoT Based Smart Public Distribution System

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1120-1122
Keyword(s):  
Distribution System ◽  
Dc Motor ◽  
Pi Controller ◽  
Raspberry Pi ◽  
Fingerprint Matching ◽  
Matching Algorithm ◽  
Public Distribution System ◽  
Minutiae Extraction ◽  
Dc Motors ◽  
The Individual

This project proposes an automatic strategy for conveyance of products to the individual card holders. The database has subtleties of commodities distribution to individual card holders. By utilizing the android phone, the clients get to their database and they can see the stock availability. The Minutiae extraction based fingerprint matching algorithm is used for identification of individual cardholders. For automatic distribution of commodities, the DC Motors are used. The Raspberry pi controller is used to control the DC Motor and to open and close the valves

scholarly journals SPY ROBOT FOR SURVEILLANCE USING RASPBERRY PI CONTROLLER .

2020 ◽  
Vol 9 (7) ◽  
pp. 173-178
Keyword(s):  
Video Streaming ◽  
Remote Monitoring ◽  
Pi Controller ◽  
Vital Role ◽  
Raspberry Pi ◽  
Main Function ◽  
Live Video ◽  
Video Information ◽  
Robot Behavior ◽  
Human Effort

Nowadays robot plays a vital role in our day to day life, thus reducing human activities. The main function of Spy robot is to roam around high sensitive region and provide video information from the required environment to the remote monitoring station. In this project, one can control the robot using Bluetooth reducing human effort. The user can continuously monitor the surrounding activities of robot location with live video streaming using wireless camera from the robot. This robot is modeled with Raspberry Pi microcontroller which control the robot behavior. The proposed spy robot is used to find smugglers infiltration.

scholarly journals Delicar: A Smart Deep Learning Based Self Driving Product Delivery Car in Perspective of Bangladesh

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 126
Author(s):  
Md. Kalim Amzad Chy ◽  
Abdul Kadar Muhammad Masum ◽  
Kazi Abdullah Mohammad Sayeed ◽  
Md Zia Uddin
Keyword(s):  
Deep Learning ◽  
Power Supply ◽  
Geographical Location ◽  
Buck Converter ◽  
Rapid Expansion ◽  
Raspberry Pi ◽  
Delivery Vehicle ◽  
Steering Angle ◽  
The Road ◽  
Product Delivery

The rapid expansion of a country’s economy is highly dependent on timely product distribution, which is hampered by terrible traffic congestion. Additional staff are also required to follow the delivery vehicle while it transports documents or records to another destination. This study proposes Delicar, a self-driving product delivery vehicle that can drive the vehicle on the road and report the current geographical location to the authority in real-time through a map. The equipped camera module captures the road image and transfers it to the computer via socket server programming. The raspberry pi sends the camera image and waits for the steering angle value. The image is fed to the pre-trained deep learning model that predicts the steering angle regarding that situation. Then the steering angle value is passed to the raspberry pi that directs the L298 motor driver which direction the wheel should follow. Based upon this direction, L298 decides either forward or left or right or backwards movement. The 3-cell 12V LiPo battery handles the power supply to the raspberry pi and L298 motor driver. A buck converter regulates a 5V 3A power supply to the raspberry pi to be working. Nvidia CNN architecture has been followed, containing nine layers including five convolution layers and three dense layers to develop the steering angle predictive model. Geoip2 (a python library) retrieves the longitude and latitude from the equipped system’s IP address to report the live geographical position to the authorities. After that, Folium is used to depict the geographical location. Moreover, the system’s infrastructure is far too low-cost and easy to install.

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