Microcontroller Based Portable Incubator Monitoring Tool with Short Message Service (SMS) notifications

The aim of this research was applied a microcontroller, temperature sensor, weight sensor, heart rate sensor and GSM module to monitoring and notification of the condition of premature babies in portable incubators. The hardware used consists of a DS18B20 sensor, Load Cell, Pulse Heart Rate Sensor, Buzzer, LCD and SIM800L Module. The results showed the Pulse sensor and DS18B20 sensor could measure and detect the baby’s heart rate and baby temperature. The result was on the LCD with an average error of 4.354% for heartrate and 1.437% for temperature. The loadcell sensor can detect weight with an error of 2.16%. The duration of sending SMS to Smartphone is 8s for each delivery. SMS was sent if the baby weak and critical condition.

IoT based smart ferry system

This research work discusses an IoT based smart ferry system. The proposed system is implemented in NODE Red based simulations. Each component is considered as nodes and analysis is done. The technical process is explained with the help of a flowchart. And how the information is passed on to the sailors, ferry crew, ferry operators, ferry controllers and maintenance engineer is discussed. In addition it is displayed using the Node red dashboard as well as through ThingSpeak cloud server for further analysis. The proposed idea is to build an IoT infrastructure consisting of smart devices which will measure different attributes of a boat and notify the captain or the rescue team of the difficulties or the problem faced by the boat during a trip. The monitoring system is based on open source software to retrieve data from the sensors at intervals and send them to the cloud in order to easily monitor them via a dashboard. Fully automated and robust IOT enabled smart devices are developed to collect the data from the boat. The Data to measure the weight and passenger on board is collected by Weight Sensor and IR Sensor and the Captain of the Ship is notified for the same. Temperature of the engine room is monitored and under severe circumstances the rescue team is notified for the same. The wind speed is also monitored in case of stormy conditions.

A Smart System to Ease Occurrence of Bedsores

The occurrence of bedsores in Ghanaian hospitals, elderly homes or care homes is especially high among patients or people who are incapacitated and cannot move or turn on their own, and who happen to remain in a particular posture for a very long time. Patients in coma, those operated on and for that matter in critical state, and patients confined to wheelchairs are primary examples. Constant pressure on some parts of the body leads to the occurrence of pressure sores or ulcers. This paper seeks to implement a Bedsore Easing System (BeSoSys) that integrate several embedded hardware components, a database and software to reduce the occurrence of bedsores. These embedded hardware components include the Bed Device Unit (BDU), the Pocket Device Unit (PDU), a pressure or weight sensor, a temperature sensor, and an inflation-deflation device. The BDU is fitted into the bed of the patient or on the surface of skin contact of the patient. The PDU is assigned to nurses or caretakers to serve as an alarm system for patient repositioning depending on situation. All activities in the Bedsore Easing System are logged into a database for future references. A bedridden patient exerts constant pressure on the bony protrusions of the body, and this causes bedsores. It was found out during the research that in Ghana, the nurses or caretakers used to turn and massage patients at some random time intervals as a way of preventing bedsores. This traditional way of turning and massaging patients is not only tedious but also ineffective. This paper seeks to provide easy, better, and effective solution to ease bedsores. The BeSoSys intends to prevent the occurrence of bedsores hence the alleviation of bedsore complications

Energy-Efficient Wireless Weight Sensor for Remote Beehive Monitoring

This paper proposes a new approach to the construction of an autonomous weight sensor for electronic beehive scales, constituting a crucial part in equipment used in the modern beekeeping economy. The main goal of this work is to demonstrate a methodology at the preliminary design stage leading to saving scarce energy resources necessary for the remote operation of a wireless network of beehives. The main findings of the work, achieved results, and identified threats for beekeeping scales operating in the real environment are also shown. The results presented in the article are based on actual data collected and recorded from several dozen beekeeping scales operating in the natural environment over a period of several years.

Digital Garbage System using Arduino NANO

Garbage bins or dust bins are those that are put in public places in cities and are currently overflowing due to an increase in waste every day. It harms people's health by spreading deadly infections. To avoid this, smart bins will be designed with sensors such as an infrared sensor, a weight sensor, a photoelectric sensor, and radio frequency identification (RFID) card reader. If someone throws trash into the smart bins, a photoelectric sensor will identify the clear representation objects, and a weight sensor will be positioned beneath the smart bin to calculate the percentage of garbage present it will forward the information to the authorities in charge of that specific location. As a result, the relevant authorities can get messages until the bin is squished, and each bin is assigned a unique ID, which will appear on the screen of the respected officer, allowing them to take fast action. If a person is within two meters radius of the bin that contains an RFID CARD READER, the RFID reader will read all of that person's information and send a message to him about what they placed into the bin, as well as an appreciation message for using the bin. Keywords: Arduino NANO, GSM Module, Smart Dustbin, IoT, Arduino Uno.

Smart Shopping with Smart Cart

Every day, huge numbers of consumers come to shop for numerous goods at mall round the world. lately, shoppers use a handcart or basket when buying the groceries at a mall . additionally, the procurement of products involves a classy process during which the purchasers must bring the items they have to urge to the check-out area, then stand and wait during an extended line so as that the products are often scanned, the whole amount calculated and thus the bill paid. As a results of this problem, this research study presents the event of a sensible cart for smart shopping. A barcode tag is found on every item during a mall , and therefore the smart cart will include a barcode reader on a cart also as cart has its own serial number in order that every cart can identified uniquely and cashier also can keep a track on the item inserted in cart . customer also can scan using his/her mobile devices through application the serial number given on smart cart and track the small print of things added in cart and parallely customer can ask queries also as can give feedback of products and item. While shopping, customers can scan the products then place them within the basket or cart, and therefore the mobile device will record and display the worth and name of every item. Also, the basket will have a weight sensor system which may confirm the accurate pricing of produce during the shopping process. Calculation of the whole cost of the customer's groceries are getting to be performed and stored within the memory of the smart basket's microcontroller. This data are getting to be sent from the basket to the foremost computer's server via a transmitter. Therefore, the proposed smart basket will allow shoppers to avoid waiting in line and having to constantly believe the number of money they go to need to spend.

Metode Fuzzy Logic pada Sistem Pemantauan dan Pemberian Pakan Kucing Berbasis Smartphone

AbstrakKucing merupakan hewan peliharan yang perlu diberi pakan secara rutin oleh pemiliknya karena ada sebagian kucing yang mudah terserang penyakit dikarenakan pola makan yang tidak teratur. Untuk mengatasinya, penelitian ini mengusulkan membangun sistem kecerdasan buatan untuk memberi pakan kucing secara terjadwal serta mengetahui kondisi kesehatan kucing dengan memanfaatkan Raspberry Pi, sensor berat dan sensor gerak dengan masukan dari sensor yang telah terpasang di sekitar tempat pakan kucing. Data yang didapat berupa data pakan yang dihabiskan kucing dan data gerak kucing kemudian diterapkan metode fuzzy logic Sugeno untuk menentukan kondisi kesehatan kucing. Dari hasil penelitian didapatkan nilai status sebesar 71%, 76% dan 80% untuk masing-masing kucing. Nilai tersebut termasuk kedalam kategori kondisi kucing sehat sehingga tindakan yang dilakukan pemilik yaitu menjaga pola makan kucing. Pada smartphone ditampilkan informasi mengenai data pakan kucing, status, dan kondisi kesehatan kucing.Kata Kunci: kesehatan kucing, Raspberry Pi, kecerdasan buatan, fuzzy logic Sugeno, smartphone.AbstractCats is one kind of pets that need to be fed regularly by their owners because some cats are susceptible to disease due to their irregular diet. This research proposes to build an artificial intelligence system to provide cat food regularly and can determine the health condition of cats, this system was built using the Raspberry Pi, weight sensor and motion sensor with input from the sensors that has been installed around the cat feed area. The data obtained in the form of feed data consumed by cats and cat motion data then Sugeno fuzzy logic method is applied to determine the health condition of the cat. From the results, each cat has a status value of 71%, 76% and 80%. This status value is included in the category of a healthy cat condition so the action taken by owners is to maintain the cat's diet. The smartphone displays information about cat feed data, status and health conditions of cats.Keywords: cat health, Raspberry Pi, fuzzy logic Sugeno, artificial intelligence, smartphone.

Classifying Co-Resident Computer Programs Using Information Revealed by Resource Contention

Modern computer architectures are complex, containing numerous components that can unintentionally reveal system operating properties. Defensive security professionals seek to minimize this kind of exposure while adversaries can leverage the data to attain an advantage. This paper presents a novel covert interrogator program technique using light-weight sensor programs to target integer, floating point, and memory units within a computer's architecture to collect data which can be used to match a running program to a known set of programs with up to 100\% accuracy under simultaneous multithreading conditions. This technique is applicable to a broad spectrum of architectural components, does not rely on specific vulnerabilities, nor requires elevated privileges. Furthermore, this research demonstrates the technique in a system with operating system containers intended to provide isolation guarantees which limit a user's ability to observe the activity of other users. In essence, this research exploits observable noise that is present whenever a program executes on a modern computer. This paper presents interrogator program design considerations, a machine learning approach to identify models with high classification accuracy, and measures the effectiveness of the approach under a variety of program execution scenarios.