Deepali Javale

Bio: Deepali Javale is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Wireless network & Deep learning. The author has an hindex of 3, co-authored 8 publications receiving 38 citations. Previous affiliations of Deepali Javale include College of Engineering, Pune & Savitribai Phule Pune University.

Smart water dripping system for agriculture/farming

Abstract: Water scarcity has been a big issue for agriculture. This proposed idea is beneficial to the farmers to irrigate the farms efficiently using an automated irrigation system based on soil temperature, moisture and pH. Respective sensors are used to find the soil water content level and based on this microcontroller drives the servo motor and pump. Irrigation status is updated to the database using PC. This technique works by installing sensors in the field to monitor the soil temperature, moisture and type of soil, which transmits the data to the microcontroller for estimation of accurate quantity of water as per the requirements. The collected data is updated from time to time to the server and can be accessed via an Android app. The subsequent watering of plants can be controlled using the aforementioned app. Depending upon the type of soil and crop, the fertilizers are suggested by applying Naive Bayes algorithm on the database. The estimated amount of rain is predicted using weather forecasting using Web scraper and the crops are watered accordingly, i.e., is a heavy rainfall is predicted then the system will automatically reduce the water supplied to the crops.

Performance evaluation of wireless image transmission: An approach using embedded system

Abstract: For the latest development in the direction of embedded system and wireless network, this project work describes wireless image transmission based on the embedded system. The Project Work Includes Following Features of Image Transmission using WIFI from S3C2440A to PC, S3C2440A is the h/w, with QTOPIA OS, PC with LINUX(Ubuntu) and with Socket code being in C/C++ language. Here S3C2440A will be working as Server and PC with Linux Platform(UBUNTU) will be working as Client. Experimental results show the throughput, transmission time and delay evaluation for various image file types along with speed gain using image compression.

Smart Detection of Parking Rates and Determining the Occupancy

Abstract: The paid parking services are increasing in demand given the ever-increasing commuters day by day. As a result, these paid parking services must incorporate the dynamics of nearby surroundings to determine the optimal parking rates. This paper demonstrates a model which will make the paid parking areas smarter by integrating the latest innovation of electronic sensors to the life-changing power of IoT. This paper determines the optimal parking rate that any parking space must have. The optimal rate calculation depends on various dependent and independent factors of parking slots like kind of day, current occupancy and impact of nearby parking slots. The model also focuses on predicting the future occupancy in the parking area, thereby describing that at any given time, what is the future occupancy of the parking slot by taking into account the previous occupancy history of the parking slot through machine learning. The parking system uses Raspberry Pi and LED sensors and android/IOS mobile application system for the end users.

A New Approach to Wireless Data Transmission Using Visible Light

Abstract: Wireless Communication has established itself as an efficient and reliable medium for data transfer. But with the number of end users increasing exponentially and the availability of radio spectrum diminishing at a fast pace there is a need of an alternate approach for data transfer. The optical wireless communication proves to be an efficient alternate solution to solve the radio frequency spectrum crisis and also to overcome the constraints of the Wireless-Fidelity (Wi-Fi) technology. The LEDs used in our daily lives for the purpose of providing light when integrated with Li-Fi technology can make an efficient communication network for data transfer. This paper proposes cost-effective and working application of the Li-Fi technology to overcome the constraints of the existing data transmission technologies and to provide an alternate data transmission medium which is built on the existing infrastructure.

Energy Efficient & Secured Data Routing Through Aggregation Node in WSN

Abstract: In Wireless Sensor Networks (WSNs), energy consumption is the most challenging issue. The more energy is consumed during captured data transmission than the local data processing at sensor nodes. Because of this reason network lifetime is reduces. Sometimes attacker nodes are also responsible of energy wastage. Data aggregation technique is one of the solutions for this issues of network lifetime and energy loss. In this paper data aggregation technique is used for detecting attack and prevention technique. For collecting the data from the cluster head in the network, system used aggregator Node (AN). If the cluster head (CH) becomes attacker, then AN recover the data from all cluster members, So that the energy in not wasted and packet drop ratio is also minimized. Also, system makes use of the Iterative Filtering (IF) algorithm, which additionally gives trust evaluation to the numerous sources from where the information is aggregated. This IF algorithm is used to detect the Simple attack and Collusion attack on nodes. The proposed system can detect the attack on all nodes including cluster member, cluster head and aggregator node. Additionally this system check data truthfulness on cluster head when data is received from all cluster members. SHAl algorithm is used for integrity checking. Experimental results prove that the proposed system improves the energy utilization, memory management and security of data along with attack detection on CH.

IoT-Based Smart Irrigation Systems: An Overview on the Recent Trends on Sensors and IoT Systems for Irrigation in Precision Agriculture

Abstract: Water management is paramount in countries with water scarcity. This also affects agriculture, as a large amount of water is dedicated to that use. The possible consequences of global warming lead to the consideration of creating water adaptation measures to ensure the availability of water for food production and consumption. Thus, studies aimed at saving water usage in the irrigation process have increased over the years. Typical commercial sensors for agriculture irrigation systems are very expensive, making it impossible for smaller farmers to implement this type of system. However, manufacturers are currently offering low-cost sensors that can be connected to nodes to implement affordable systems for irrigation management and agriculture monitoring. Due to the recent advances in IoT and WSN technologies that can be applied in the development of these systems, we present a survey aimed at summarizing the current state of the art regarding smart irrigation systems. We determine the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions. We provide an overview of the most utilized nodes and wireless technologies. Lastly, we will discuss the challenges and the best practices for the implementation of sensor-based irrigation systems.

Adoption of the Internet of Things (IoT) in Agriculture and Smart Farming towards Urban Greening: A Review

Abstract: It is essential to increase the productivity of agricultural and farming processes to improve yields and cost-effectiveness with new technology such as the Internet of Things (IoT). In particular, IoT can make agricultural and farming industry processes more efficient by reducing human intervention through automation. In this study, the aim to analyze recently developed IoT applications in the agriculture and farming industries to provide an overview of sensor data collections, technologies, and sub-verticals such as water management and crop management. In this review, data is extracted from 60 peer-reviewed scientific publications (2016-2018) with a focus on IoT sub-verticals and sensor data collection for measurements to make accurate decisions. Our results from the reported studies show water management is the highest sub-vertical (28.08%) followed by crop management (14.60%) then smart farming (10.11%). From the data collection, livestock management and irrigation management resulted in the same percentage (5.61%). In regard to sensor data collection, the highest result was for the measurement of environmental temperature (24.87%) and environmental humidity (19.79%). There are also some other sensor data regarding soil moisture (15.73%) and soil pH (7.61%). Research indicates that of the technologies used in IoT application development, Wi-Fi is the most frequently used (30.27%) followed by mobile technology (21.10%). As per our review of the research, we can conclude that the agricultural sector (76.1%) is researched considerably more than compared to the farming sector (23.8%). This study should be used as a reference for members of the agricultural industry to improve and develop the use of IoT to enhance agricultural production efficiencies. This study also provides recommendations for future research to include IoT systems' scalability, heterogeneity aspects, IoT system architecture, data analysis methods, size or scale of the observed land or agricultural domain, IoT security and threat solutions/protocols, operational technology, data storage, cloud platform, and power supplies.

A comprehensive review of Data Mining techniques in smart agriculture

Abstract: Agriculture remains a vital sector for most countries. It presents the main source of food for the population of the world. However, it faces a big challenge: producing more and better while increasing the sustainability with a reasonable use of natural resources, reducing environmental degradation as well as adapting to climate change. Hence, it is extremely important to switch from traditional agricultural methods to modern agriculture. Smart Agriculture is one of the solutions to deal with the growing demand for food while meeting sustainability requirements. In Smart Agriculture, the role of information is increasing. Information on weather conditions, soils, diseases, insects, seeds, fertilizers, etc. constitutes an important contribution to the economic and sustainable development of this sector. Smart management consists of collecting, transmitting, selecting and analyzing data. As the amount of agricultural data increases significantly, robust analytical techniques capable of processing and analyzing large amounts of data to obtain more reliable information and much more accurate predictions are essential. Data Mining is expected to play an important role in Smart Agriculture for managing real-time data analysis with massive data. The aim of this paper is to review ongoing studies and research on smart agriculture using the recent practice of Data Mining, to solve a variety of agricultural problems.