Procedural involute spur gears in Blender 3 with geometry nodes
I love designing functional models for 3D printing with Blender. I know it’s not a common choice and CAD software is usually preferred, and I have tested many but none has offered me the flexibility and speed of Blender for my projects. One issue that I always had was generating gears and bolts. Of course […]
Taking advantage of ZFS for smarter Proxmox backups
Let’s say we have a Proxmox cluster running ~30 VMs using ZFS as a storage backend. We want to backup each VM hourly to a remote server, and then replicate these backups to an offsite server. Proxmox Backup Server is nicely integrated into PVE’s web GUI, and can work with ZFS volumes. However, PBS is […]
3D printed Duplo-compatible locomotive
Download on printables.com This locomotive can fit on lego duplo tracks. Blender files are provided for adjustments. Required hardware :
Gérez les maraudes sociales de votre association avec NosMaraudes
L’application NosMaraudes développée par GM CRD est la solution idéale pour votre association.
Comparer DPE et consommation a-t-il un sens ?
Récapitulatif des publications à ce sujet : Hello Watt a publié le 4 janvier une étude concluant à un manque de corrélation entre le DPE d’un logement, censé évaluer sa performance énergétique, et sa consommation d’énergie mesurée par les compteurs communicants. Pourquoi cette étude ? Dans sa mission de favoriser la transition énergétique des ménages, […]
Proxmox cluster on distant bare metal servers
I run a Proxmox cluster with three nodes that are set up on three rented bare-metal servers from OVH in different datacenters. This is a pretty unusual setup, because bare-metal rental companies to not allow bridging on their network interface. Bridging in a typical racked cluster In this context, bridging means that a single physical […]
Repairing a key fob with a broken button
A family member mentioned that she had a broken key fob for her garage door, in which the left button was inoperative. It seemed very likely that the switch itself was broken, so I offered to replace it. However, I did not have time to source a new switch, so I opted to wire a […]
Predicting Home Energy Consumption, the Data-Driven Way
At Hello Watt, we help residential energy consumers reduce their energy bills through various means. This involves estimating their electricity and gas consumption based on information we collect either over the phone or through a form. We developed Consumption Calculator, a new model that works very similarly to the previous model except its coefficients are optimized automatically based on training data derived from our database.
Domain Knowledge Aids in Signal Disaggregation; the Example of the Cumulative Water Heater
In this article we present an unsupervised low-frequency method aimed at detecting and disaggregating the power used by Cumulative Water Heaters (CWH) in residential homes. Our model circumvents the inherent difficulty of unsupervised signal disaggregation by using both the shape of a power spike and its temporal pattern to identify the contribution of CWH reliably. Indeed, many CHWs in France are configured to turn on automatically during off-peak hours only, and we are able to use this domain knowledge to aid peak identification despite the low sampling frequency. In order to test our model, we equipped a home with sensors to record the ground truth consumption of a water heater. We then apply the model to a larger dataset of energy consumption of Hello Watt users consisting of one month of consumption data for 5k homes at 30-minute resolution. In this dataset we successfully identified CWHs in 66.5% of cases where consumers declared using them. Inability of our model to identify CWHs in the consumption signal in the remaining cases is likely due to possible misconfiguration of CWHs, since triggering them during off-peak hours requires specific wiring in the electrical panel of the house. Our model, despite its simplicity, offers promising applications: detection of mis-configured CWHs on off-peak contracts and slow performance degradation.
Video and motion analysis with Skope
Over 2020 and 2021 I did hardware and software prototyping for Sites Technologies, using Raspberry Pi cameras with video processing, and IMU sensors with machine learning. This project also involved server infrastructure.